{"schema_version":"onlylabs.public_analysis_evidence.v1","title":"Mistral AI analysis evidence pack","description":"Public onlylabs evidence pack for cited agent analysis: captured pages, ranked public signals, and stored web-search provenance used by the background analysis workflow.","url":"https://onlylabs.fyi/analysis/mistral","json_url":"https://onlylabs.fyi/analysis/mistral/evidence.json","generated_at":"2026-06-11T18:06:13.891Z","org":{"slug":"mistral","name":"Mistral AI","category":"frontier-lab","category_label":"Frontier lab","dossier_url":"https://onlylabs.fyi/labs/mistral"},"analysis":{"url":"https://onlylabs.fyi/analysis/mistral","json_url":"https://onlylabs.fyi/analysis/mistral/analysis.json","generated_at":"2026-06-08T15:59:09.295+00:00"},"workflow":{"version":"synthesize-analyses","provider":null,"model":null,"agent":null,"public_pack_mode":"local-pages-and-events","live_web_fetches":false,"note":"Public evidence exports do not trigger live Exa calls; stored Exa provenance is included when analysis metadata contains it."},"stats":{"pages":28,"events":140,"web":0,"evidence":88,"signal_desks":{"hiring":29,"forks":1,"releases":28,"talking":0,"repos":2},"data_radar_lanes":{"data":0,"evals":0,"infrastructure":6,"safety":2,"product":15},"data_radar_matches":20,"stored_analysis_evidence":null,"stored_analysis_web":null,"stored_analysis_signal_desks":null,"stored_analysis_data_radar_lanes":null,"stored_analysis_data_radar_matches":null},"stored_web_provenance":null,"evidence":[{"ref":"P1","kind":"page","title":"mistralai/mistral-inference repository metadata","date":"2026-06-11T03:59:01.586759+00:00","date_source":null,"source_url":"https://github.com/mistralai/mistral-inference","signal_url":null,"signal_json_url":null,"text":"# mistralai/mistral-inference\n\nDescription: Official inference library for Mistral models\n\nLanguage: Jupyter Notebook\n\nLicense: Apache-2.0\n\nStars: 10813\n\nForks: 1052\n\nOpen issues: 175\n\nCreated: 2023-09-27T13:05:24Z\n\nPushed: 2026-04-20T10:10:46Z\n\nDefault branch: main\n\nFork: no\n\nArchived: yes\n\nREADME:\n# Mistral Inference\n<a target=\"_blank\" href=\"https://colab.research.google.com/github/mistralai/mistral-inference/blob/main/tutorials/getting_started.ipynb\">\n<img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/>\n</a>\n\nThis repository contains minimal code to run Mistral models.\n\nBlog 7B: [https://mistral.ai/news/announcing-mistral-7b/](https://mistral.ai/news/announcing-mistral-7b/)\\\nBlog 8x7B: [https://mistral.ai/news/mixtral-of-experts/](https://mistral.ai/news/mixtral-of-experts/)\\\nBlog 8x22B: [https://mistral.ai/news/mixtral-8x22b/](https://mistral.ai/news/mixtral-8x22b/)\\\nBlog Codestral 22B: [https://mistral.ai/news/codestral](https://mistral.ai/news/codestral/) \\\nBlog Codestral Mamba 7B: [https://mistral.ai/news/codestral-mamba/](https://mistral.ai/news/codestral-mamba/) \\\nBlog Mathstral 7B: [https://mistral.ai/news/mathstral/](https://mistral.ai/news/mathstral/) \\\nBlog Nemo: [https://mistral.ai/news/mistral-nemo/](https://mistral.ai/news/mistral-nemo/) \\\nBlog Mistral Large 2: [https://mistral.ai/news/mistral-large-2407/](https://mistral.ai/news/mistral-large-2407/) \\\nBlog Pixtral 12B: [https://mistral.ai/news/pixtral-12b/](https://mistral.ai/news/pixtral-12b/)\nBlog Mistral Small 3.1: [https://mistral.ai/news/mistral-small-3-1/](https://mistral.ai/news/mistral-small-3-1/)\n\nDiscord: [https://discord.com/invite/mistralai](https://discord.com/invite/mistralai)\\\nDocumentation: [https://docs.mistral.ai/](https://docs.mistral.ai/)\\\nGuardrailing: [https://docs.mistral.ai/usage/guardrailing](https://docs.mistral.ai/usage/guardrailing)\n\n## Installation\n\nNote: You will use a GPU to install `mistral-inference`, as it currently requires `xformers` to be installed and `xformers` itself needs a GPU for installation.\n\n### PyPI\n\n```\npip install mistral-inference\n```\n\n### Local\n\n```\ncd $HOME && git clone https://github.com/mistralai/mistral-i"},{"ref":"P2","kind":"page","title":"mistralai/client-python repository metadata","date":"2026-06-11T03:59:01.571325+00:00","date_source":null,"source_url":"https://github.com/mistralai/client-python","signal_url":null,"signal_json_url":null,"text":"# mistralai/client-python\n\nDescription: Python client library for Mistral AI platform\n\nLanguage: Python\n\nLicense: Apache-2.0\n\nStars: 745\n\nForks: 194\n\nOpen issues: 18\n\nCreated: 2023-12-07T10:09:51Z\n\nPushed: 2026-06-10T22:13:43Z\n\nDefault branch: main\n\nFork: no\n\nArchived: no\n\nREADME:\n# Mistral Python Client\n\n## Migrating from v1\n\nIf you are upgrading from v1 to v2, check the [migration guide](https://github.com/mistralai/client-python/blob/main/MIGRATION.md) for details on breaking changes and how to update your code.\n\n## API Key Setup\n\nBefore you begin, you will need a Mistral AI API key.\n\n1. Get your own Mistral API Key: <https://docs.mistral.ai/#api-access>\n2. Set your Mistral API Key as an environment variable. You only need to do this once.\n\n```bash\n# set Mistral API Key (using zsh for example)\n$ echo 'export MISTRAL_API_KEY=[your_key_here]' >> ~/.zshenv\n\n# reload the environment (or just quit and open a new terminal)\n$ source ~/.zshenv\n```\n\n<!-- Start Summary [summary] -->\n## Summary\n\nMistral AI API: Our Chat Completion and Embeddings APIs specification. Create your account on [La Plateforme](https://console.mistral.ai) to get access and read the [docs](https://docs.mistral.ai) to learn how to use it.\n<!-- End Summary [summary] -->\n\n<!-- Start Table of Contents [toc] -->\n## Table of Contents\n<!-- $toc-max-depth=2 -->\n* [Mistral Python Client](#mistral-python-client)\n* [Migrating from v1](#migrating-from-v1)\n* [API Key Setup](#api-key-setup)\n* [SDK Installation](#sdk-installation)\n* [SDK Example Usage](#sdk-example-usage)\n* [Providers' SDKs Example Usage](#providers-sdks-example-usage)\n* [Available Resources and Operations](#available-resources-and-operations)\n* [Server-sent event streaming](#server-sent-event-streaming)\n* [Pagination](#pagination)\n* [File uploads](#file-uploads)\n* [Retries](#retries)\n* [Error Handling](#error-handling)\n* [Server Selection](#server-selection)\n* [Custom HTTP Client](#custom-http-client)\n* [Authentication](#authentication)\n* [Resource Management](#resource-management)\n* [Debugging](#debugging)\n* [IDE Support](#ide-support)\n* [Development](#development)\n* [Contributions](#contributions)\n\n<!-- End Table of Contents [toc] -->\n\n<!--"},{"ref":"P3","kind":"page","title":"mistralai/client-js repository metadata","date":"2026-06-11T03:59:01.566556+00:00","date_source":null,"source_url":"https://github.com/mistralai/client-js","signal_url":null,"signal_json_url":null,"text":"# mistralai/client-js\n\nDescription: JS Client library for Mistral AI platform\n\nLanguage: JavaScript\n\nLicense: Apache-2.0\n\nStars: 203\n\nForks: 47\n\nOpen issues: 0\n\nCreated: 2023-12-07T10:40:00Z\n\nPushed: 2024-10-10T11:16:49Z\n\nDefault branch: main\n\nFork: no\n\nArchived: yes\n\nREADME:\n# 📢🚨 This repository is now archived 📢🚨\n\nWe have deprecated this package in favor of [mistralai/client-ts](https://github.com/mistralai/client-ts), which is the new official Mistral client, compatibile with both Typescript and Javascript.\n\nYou can find all installation information [here](https://github.com/mistralai/client-ts?tab=readme-ov-file#sdk-installation).\n\nThis change is effective starting with version 1.0.0 of the [npm package](https://www.npmjs.com/package/@mistralai/mistralai?activeTab=readme).\n\n--- \n\nThis JavaScript client is inspired from [cohere-typescript](https://github.com/cohere-ai/cohere-typescript)\n\n# Mistral JavaScript Client\n\nYou can use the Mistral JavaScript client to interact with the Mistral AI API.\n\n## Installing\n\nYou can install the library in your project using:\n\n`npm install @mistralai/mistralai`\n\n## Usage\n\nYou can watch a free course on using the Mistral JavaScript client [here.](https://scrimba.com/links/mistral)\n\n### Set up\n\n```typescript\nimport MistralClient from '@mistralai/mistralai';\n\nconst apiKey = process.env.MISTRAL_API_KEY || 'your_api_key';\n\nconst client = new MistralClient(apiKey);\n```\n\n### List models\n\n```typescript\nconst listModelsResponse = await client.listModels();\nconst listModels = listModelsResponse.data;\nlistModels.forEach((model) => {\nconsole.log('Model:', model);\n});\n```\n\n### Chat with streaming\n\n```typescript\nconst chatStreamResponse = await client.chatStream({\nmodel: 'mistral-tiny',\nmessages: [{role: 'user', content: 'What is the best French cheese?'}],\n});\n\nconsole.log('Chat Stream:');\nfor await (const chunk of chatStreamResponse) {\nif (chunk.choices[0].delta.content !== undefined) {\nconst streamText = chunk.choices[0].delta.content;\nprocess.stdout.write(streamText);\n}\n}\n```\n\n### Chat without streaming\n\n```typescript\nconst chatResponse = await client.chat({\nmodel: 'mistral-tiny',\nmessages: [{role: 'user', content: 'What is the bes"},{"ref":"P4","kind":"page","title":"mistralai/platform-docs-public repository metadata","date":"2026-06-11T03:59:01.479683+00:00","date_source":null,"source_url":"https://github.com/mistralai/platform-docs-public","signal_url":null,"signal_json_url":null,"text":"# mistralai/platform-docs-public\n\nLanguage: MDX\n\nLicense: Apache-2.0\n\nStars: 67\n\nForks: 125\n\nOpen issues: 63\n\nCreated: 2023-12-22T17:21:55Z\n\nPushed: 2026-06-09T08:54:18Z\n\nDefault branch: main\n\nFork: no\n\nArchived: no\n\nREADME:\n# Mistral AI LLM documentation\n\nThis folder contains the documentation of the Mistral LLM setup and APIs.\n\nPlease follow the following steps to ensure your changes can be deployed\nsuccessfully.\n\n## Cloning the Project\n\nTo clone the Mistral AI LLM project, including all necessary submodules, follow these steps:\n\n1. **Clone the Repository**: Use the `--recurse-submodules` flag to ensure all submodules are cloned along with the main repository:\n\n```bash\ngit clone --recurse-submodules <repository-url>\n```\n\n2. **Navigate to the Project Directory**: After cloning, navigate into the project directory:\n\n```bash\ncd <project-directory>\n```\n\n3. **Verify Submodules**: Ensure that all submodules are initialized and updated:\n```bash\ngit submodule update --init --recursive\n```\n\nEnsure that you commit any changes to submodules to keep the repository consistent.\n\n## Project Setup\n\nYou will need to install `pnpm` and `node` first. For example, if you are using Mac, You can install [Homebrew](https://brew.sh/) and then install `pnpm` and `node`:\n\n```\nbrew install pnpm\nbrew install node\n```\n\n### Installation\n\n```bash\npnpm install\n```\n\n### Local Development\n\n```bash\npnpm dev\n```\n\nThis command starts a local development server at `http://localhost:3000`. Most changes are reflected live without having to restart the server.\n\n### Build\n\n```bash\npnpm build\n```\n\nThis command generates a production build in the `.next` directory.\n\n### Cookbooks\n\nYou can add a cookbook in the docs by adding a cookbook object to the `cookbooks.config.json` file:\n\n```json\n{\n\"path\": \"your/path/your-file-name.ipynb\",\n\"labels\": {\n\"integrations\": [],\n\"useCases\": [\n\"Your use case\"\n]\n},\n\"availableInDocs\": \"True\", \n\"title\": \"\",\n\"mainSection\": {\n\"featured\": \"False\",\n\"latest\": \"True\"\n}\n}\n```\n\nIf the title is empty, the title will be extracted from the cookbook.\n\n### Troubleshoot\n\n- Make sure URLs start with `https://` or `http://`, otherwise, it will look for the relative paths in the repo.\n- Ima"},{"ref":"P5","kind":"page","title":"mistralai/cookbook repository metadata","date":"2026-06-11T03:59:01.111707+00:00","date_source":null,"source_url":"https://github.com/mistralai/cookbook","signal_url":null,"signal_json_url":null,"text":"# mistralai/cookbook\n\nLanguage: Jupyter Notebook\n\nLicense: MIT\n\nStars: 2263\n\nForks: 512\n\nOpen issues: 51\n\nCreated: 2024-01-05T10:37:21Z\n\nPushed: 2026-06-10T19:03:24Z\n\nDefault branch: main\n\nFork: no\n\nArchived: no\n\nREADME:\n# Mistral Cookbook\n\nThe Mistral Cookbook features examples contributed by Mistralers and our community, as well as our partners. If you have cool examples showcasing Mistral models, feel free to share them by submitting a PR to this repo.\n\n## Submission Guidelines:\n\n- File Format: Please submit your example in the .md or .ipynb format.\n- Runnable on Colab: If you're sharing a notebook example, try to make sure it's runnable on Google Colab.\n- Authorship: Kindly include your name, your Github handle, and affiliation at the beginning of the file.\n- Descriptions: Please include your notebook along with its category and descriptions in the table below.\n- Tone: Kindly maintain a neutral tone and minimize any excessive marketing materials.\n- Reproducibility: To ensure others can reproduce your work, kindly tag package versions in your code.\n- Image size: If you have images, please make sure each image's size is below 500KB.\n- Copyright: Always respect copyright and intellectual property laws.\n\nDisclaimer: Examples contributed by the community and partners do not represent Mistral's views and opinions.\n\n## Content Guidelines:\n\n- Originality: Is your content original and offering a fresh perspective?\n- Clear: Is your content well-structured and clearly written?\n- Value: Is your content valuable to the community? Does the community need it?\n\n## Main Notebooks\n\n| Notebook | Category | Description |\n|--------------------------------------------------------------------------------|-----------------------------|----------------------------------------------------------------------------------|\n| [quickstart.ipynb](quickstart.ipynb) | chat, embeddings | Basic quickstart with chat and embeddings with Mistral AI API |\n| [prompting_capabilities.ipynb](mistral/prompting/prompting_capabilities.ipynb) | prompting | Write prompts for classification, summarization, personalization, and evaluation |\n| [basic_RAG.ipynb](mistral/rag/basic_RAG.ipynb) | RAG | RAG from scr"},{"ref":"P6","kind":"page","title":"mistralai/mistral-common repository metadata","date":"2026-06-11T03:59:00.768055+00:00","date_source":null,"source_url":"https://github.com/mistralai/mistral-common","signal_url":null,"signal_json_url":null,"text":"# mistralai/mistral-common\n\nDescription: Official inference library for pre-processing of Mistral models\n\nLanguage: Python\n\nLicense: Apache-2.0\n\nStars: 903\n\nForks: 146\n\nOpen issues: 7\n\nCreated: 2024-04-15T08:43:59Z\n\nPushed: 2026-06-10T09:50:39Z\n\nDefault branch: main\n\nFork: no\n\nArchived: no\n\nREADME:\n<div align=\"center\">\n\n<img src=\"./docs/assets/logo.svg\" alt=\"Mistral AI\" height=\"100\"/>\n\n<br/>\n<br/>\n\n# Mistral-common\n\n[![PyPI version](https://img.shields.io/pypi/v/mistral-common?label=release&logo=pypi&logoColor=white)](https://pypi.org/project/mistral-common/)\n[![Tests](https://img.shields.io/github/actions/workflow/status/mistralai/mistral-common/lint_build_test.yaml?label=tests&branch=main)](https://github.com/mistralai/mistral-common/actions/workflows/lint_build_test.yaml)\n[![Documentation](https://img.shields.io/website?url=https%3A%2F%2Fmistralai.github.io%2Fmistral-common%2F&up_message=online&down_message=offline&label=docs)](https://mistralai.github.io/mistral-common/)\n[![Python version](https://img.shields.io/badge/dynamic/json?query=info.requires_python&label=python&url=https%3A%2F%2Fpypi.org%2Fpypi%2Fmistral-common%2Fjson)](https://www.python.org/downloads/)\n[![License](https://img.shields.io/badge/license-Apache--2.0-blue.svg)](./LICENCE)\n\n</div>\n\n## What is it? \n\n**mistral-common** is a set of tools to help you work with [Mistral AI](https://mistral.ai/) models.\n\nWe open-source the tokenizers, validation and normalization code that can be used with our models.\n\nThis ensures that you can take full advantage of our models for the following features:\n\n- **tokenization** of text, images and tools calls.\n- **validation and normalization** of requests, messages, tool calls, and responses. This is built on top of the [Pydantic](https://docs.pydantic.dev/latest/) library.\n\nWe also version our tokenizers to guarantee backward compatibility for the models that we release.\n\n## For who ?\n\nThis library is for you if you want to:\n\n- use our models in your own application.\n- build your own models and want to use the same tokenization and validation code as we do.\n\n## How to use it ?\n\nYou can install the library using pip:\n```sh\npip install mistral-common\n```\n\nWe pro"},{"ref":"P7","kind":"page","title":"mistralai/sagemaker-docs repository metadata","date":"2026-06-11T03:59:00.570303+00:00","date_source":null,"source_url":"https://github.com/mistralai/sagemaker-docs","signal_url":null,"signal_json_url":null,"text":"# mistralai/sagemaker-docs\n\nDescription: Mistral AI documentation for SageMaker\n\nLanguage: Jupyter Notebook\n\nStars: 3\n\nForks: 4\n\nOpen issues: 1\n\nCreated: 2024-06-26T15:47:38Z\n\nPushed: 2025-04-18T08:37:36Z\n\nDefault branch: main\n\nFork: no\n\nArchived: no\n\nREADME:\n# Mistral AI on SageMaker\n\nThis repository contains code and data samples to deploy, run and fine-tune Mistral AI models on AWS SageMaker.\n\n## Getting started\n\n- Install [uv](https://docs.astral.sh/uv/getting-started/installation/)\n- Start a notebook server by running the following command:\n\n```shell\nuv run jupyter notebook\n```"},{"ref":"P8","kind":"page","title":"mistralai/client-ts repository metadata","date":"2026-06-11T03:59:00.569901+00:00","date_source":null,"source_url":"https://github.com/mistralai/client-ts","signal_url":null,"signal_json_url":null,"text":"# mistralai/client-ts\n\nDescription: TS Client library for Mistral AI platform \n\nLanguage: TypeScript\n\nLicense: Apache-2.0\n\nStars: 145\n\nForks: 41\n\nOpen issues: 15\n\nCreated: 2024-08-07T11:54:28Z\n\nPushed: 2026-06-09T13:28:46Z\n\nDefault branch: main\n\nFork: no\n\nArchived: no\n\nREADME:\n# Mistral Typescript Client\n\n> **This is v2 of the Mistral TypeScript SDK.**\n>\n> Key changes from v1: **ESM-only**, shorter type names, forward-compatible enums/unions, Zod v4.\n> See the **[Migration Guide](https://github.com/mistralai/client-ts/blob/main/MIGRATION.md)** for full details.\n>\n> To pin v1: `npm install @mistralai/mistralai@^1` · **[v1 documentation and source](https://github.com/mistralai/client-ts/tree/v1)**\n\n<!-- Start Summary [summary] -->\n## Summary\n\nMistral AI API: Our Chat Completion and Embeddings APIs specification. Create your account on [La Plateforme](https://console.mistral.ai) to get access and read the [docs](https://docs.mistral.ai) to learn how to use it.\n<!-- End Summary [summary] -->\n\n<!-- Start Table of Contents [toc] -->\n## Table of Contents\n<!-- $toc-max-depth=2 -->\n* [Mistral Typescript Client](#mistral-typescript-client)\n* [SDK Installation](#sdk-installation)\n* [Requirements](#requirements)\n* [API Key Setup](#api-key-setup)\n* [SDK Example Usage](#sdk-example-usage)\n* [Providers' SDKs](#providers-sdks)\n* [Available Resources and Operations](#available-resources-and-operations)\n* [Server-sent event streaming](#server-sent-event-streaming)\n* [Pagination](#pagination)\n* [File uploads](#file-uploads)\n* [Retries](#retries)\n* [Error Handling](#error-handling)\n* [Server Selection](#server-selection)\n* [Custom HTTP Client](#custom-http-client)\n* [Authentication](#authentication)\n* [Standalone functions](#standalone-functions)\n* [Debugging](#debugging)\n* [Development](#development)\n* [Contributions](#contributions)\n\n<!-- End Table of Contents [toc] -->\n\n<!-- Start SDK Installation [installation] -->\n## SDK Installation\n\nThe SDK can be installed with either [npm](https://www.npmjs.com/), [pnpm](https://pnpm.io/), [bun](https://bun.sh/) or [yarn](https://classic.yarnpkg.com/en/) package managers.\n\n### NPM\n\n```bash\nnpm add @mistralai/mistralai\n```\n\n### PNPM\n\n```bas"},{"ref":"P9","kind":"page","title":"mistralai/mistral-finetune repository metadata","date":"2026-06-11T03:59:00.524618+00:00","date_source":null,"source_url":"https://github.com/mistralai/mistral-finetune","signal_url":null,"signal_json_url":null,"text":"# mistralai/mistral-finetune\n\nLanguage: Python\n\nLicense: Apache-2.0\n\nStars: 3091\n\nForks: 318\n\nOpen issues: 49\n\nCreated: 2024-05-24T18:19:28Z\n\nPushed: 2025-11-21T10:27:03Z\n\nDefault branch: main\n\nFork: no\n\nArchived: no\n\nREADME:\n# Mistral-finetune\n\n<a target=\"_blank\" href=\"https://colab.research.google.com/github/mistralai/mistral-finetune/blob/main/tutorials/mistral_finetune_7b.ipynb\">\n<img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/>\n</a>\n\n`mistral-finetune` is a light-weight codebase that enables memory-efficient and performant finetuning of Mistral's models.\nIt is based on [LoRA](https://arxiv.org/abs/2106.09685), a training paradigm where most weights are frozen and only 1-2% of additional weights in the form of low-rank matrix perturbations are trained. \n\nFor maximum efficiency it is recommended to use an A100 or H100 GPU. The codebase is optimized \nfor multi-GPU-single-node training setups, but for smaller models, such as the 7B a single GPU suffices.\n\n> **Note**\n> \n> - The goal of this repository is to provide a simple, guided entrypoint to finetune Mistral models.\n> As such, it is fairly opinionated (especially around data formatting) and does not aim at being exhaustive\n> across multiple model architectures or hardware types.\n> For more generic approaches, you can check out some other great projects like \n> [torchtune](https://pytorch.org/torchtune/stable/overview.html).\n\n## News\n\n- **13.08.2024**: [Mistral Large v2](https://mistral.ai/news/mistral-large-2407/) is now compatible with `mistral-finetune`!\n- 1. Download the 123B Instruct [here](##model-download) and set `model_id_or_path` to the downloaded checkpoint dir.\n- 2. Fine-tuning Mistral-Large v2 requires significantly more memory due to a larger model size. For now set `seq_len` to <= 8192\n- 3. It is recommended to use a lower learning rate as compared to other models, *e.g.* lr=1e-6 should work well for most cases.\n\n- **19.07.2024**: [Mistral Nemo](https://mistral.ai/news/mistral-nemo/) is now compatible with `mistral-finetune`! \n- 1. Download the 12B Base or Instruct [here](##model-download) and set `model_id_or_path` to the downloaded checkpoint dir.\n- 2. "},{"ref":"P10","kind":"page","title":"mistralai/mistral-evals repository metadata","date":"2026-06-11T03:59:00.016636+00:00","date_source":null,"source_url":"https://github.com/mistralai/mistral-evals","signal_url":null,"signal_json_url":null,"text":"# mistralai/mistral-evals\n\nLanguage: Python\n\nStars: 87\n\nForks: 14\n\nOpen issues: 8\n\nCreated: 2024-09-13T18:11:29Z\n\nPushed: 2025-11-21T10:21:09Z\n\nDefault branch: main\n\nFork: no\n\nArchived: no\n\nREADME:\n# Mistral Evals\n\nThis repository contains code to run evals released by Mistral AI as well as standardized prompts, parsing and metrics computation for popular academic benchmarks.\n\n## Installation\n\n```\npip install -r requirements.txt\n```\n\n## Evals\n\nWe support the following evals in this repository:\n* `mm_mt_bench`: [MM-MT-Bench](https://huggingface.co/datasets/mistralai/MM-MT-Bench) is a multi-turn LLM-as-a-judge evaluation task released by Mistral AI that uses GPT-4o for judging model answers given reference answers.\n* `vqav2`: [VQAv2](https://huggingface.co/datasets/HuggingFaceM4/VQAv2)\n* `docvqa`: [DocVQA](https://huggingface.co/datasets/lmms-lab/DocVQA)\n* `mathvista`: [MathVista](https://huggingface.co/datasets/AI4Math/MathVista)\n* `mmmu`: [MMMU](https://huggingface.co/datasets/lmms-lab/MMMU)\n* `chartqa`: [ChartQA](https://github.com/vis-nlp/ChartQA)\n\n### Example usage:\n\n**Step 1**: Host a model using vLLM\n\nTo install vLLM, follow the directions [here](https://docs.vllm.ai/en/latest/getting_started/installation.html).\n\n```\n>> vllm serve mistralai/Pixtral-12B-2409 --config_format mistral --tokenizer_mode \"mistral\"\n```\n\n**Step 2**: Evaluate hosted model.\n```\n>> python -m eval.run eval_vllm \\\n--model_name mistralai/Pixtral-12B-2409 \\\n--url http://0.0.0.0:8000 \\\n--output_dir ~/tmp \\\n--eval_name \"mm_mt_bench\"\n```\n\n**NOTE**: Evaluating MM-MT-Bench requires calls to GPT-4o as a judge, hence you'll need\nto set the `OPENAI_API_KEY` environment variable for the eval to work.\n\nFor evaluating the other supported evals, see the **Evals** section.\n\n#### Evaluating a non-vLLM model\n\nTo evaluate your own model, you can also create a `Model` class which implements a `__call__` method which takes as input a chat completion request and returns a string answer. Requests are provided in [vLLM API format](https://docs.vllm.ai/en/latest/models/vlm.html#openai-vision-api).\n\n```\nclass CustomModel(Model):\n\ndef __call__(self, request: dict[str, Any]):\n# Your model code\n...\nreturn answer\n``"},{"ref":"P11","kind":"page","title":"mistralai/mistral-vibe repository metadata","date":"2026-06-11T03:58:59.720623+00:00","date_source":null,"source_url":"https://github.com/mistralai/mistral-vibe","signal_url":null,"signal_json_url":null,"text":"# mistralai/mistral-vibe\n\nDescription: Minimal CLI coding agent by Mistral\n\nLanguage: Python\n\nLicense: Apache-2.0\n\nStars: 4435\n\nForks: 525\n\nOpen issues: 263\n\nCreated: 2025-12-08T18:56:59Z\n\nPushed: 2026-06-08T13:00:20Z\n\nDefault branch: main\n\nFork: no\n\nArchived: no\n\nREADME:\n# Mistral Vibe\n\n[![PyPI Version](https://img.shields.io/pypi/v/mistral-vibe)](https://pypi.org/project/mistral-vibe)\n[![Python Version](https://img.shields.io/badge/python-3.12%2B-blue)](https://www.python.org/downloads/release/python-3120/)\n[![CI Status](https://github.com/mistralai/mistral-vibe/actions/workflows/ci.yml/badge.svg)](https://github.com/mistralai/mistral-vibe/actions/workflows/ci.yml)\n[![License](https://img.shields.io/github/license/mistralai/mistral-vibe)](https://github.com/mistralai/mistral-vibe/blob/main/LICENSE)\n\n```\n██████████████████░░\n██████████████████░░\n████ ██████ ████░░\n████ ██ ████░░\n████ ████░░\n████ ██ ██ ████░░\n██ ██ ██░░\n██████████████████░░\n██████████████████░░\n```\n\n**Mistral's open-source CLI coding assistant.**\n\nMistral Vibe is a command-line coding assistant powered by Mistral's models. It provides a conversational interface to your codebase, allowing you to use natural language to explore, modify, and interact with your projects through a powerful set of tools.\n\n> [!WARNING]\n> Mistral Vibe works on Windows, but we officially support and target UNIX environments.\n\n### One-line install (recommended)\n\n**Linux and macOS**\n\n```bash\ncurl -LsSf https://mistral.ai/vibe/install.sh | bash\n```\n\n**Windows**\n\nFirst, install uv\n\n```bash\npowershell -ExecutionPolicy ByPass -c \"irm https://astral.sh/uv/install.ps1 | iex\"\n```\n\nThen, use uv command below.\n\n### Using uv\n\n```bash\nuv tool install mistral-vibe\n```\n\n### Using pip\n\n```bash\npip install mistral-vibe\n```\n\n## Table of Contents\n\n- [Features](#features)\n- [Built-in Agents](#built-in-agents)\n- [Subagents and Task Delegation](#subagents-and-task-delegation)\n- [Interactive User Questions](#interactive-user-questions)\n- [Terminal Requirements](#terminal-requirements)\n- [Quick Start](#quick-start)\n- [Usage](#usage)\n- [Interactive Mode](#interactive-mode)\n- [Trust Folder System](#trust-folder-system)\n- [Programmatic Mode](#prog"},{"ref":"P12","kind":"page","title":"Legal Tech & Ops Associate (IP & Licensing Business)","date":"2026-06-11T03:48:28.844+00:00","date_source":null,"source_url":"https://jobs.lever.co/mistral/bd69355b-9159-4bad-b52d-b71110e65090","signal_url":null,"signal_json_url":null,"text":"Mistral AI - Legal Tech & Ops Associate (IP & Licensing Business)\n\n## Legal Tech & Ops Associate (IP & Licensing Business)\n\nPalo Alto\n\nLegal /\n\nFull-time /\n\nOn-site\n\napply for this job\n\nAbout Mistral\n\nAt Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.\n\nWe democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise as well as personal needs. Our offerings include Le Chat, AI Studio, Mistral Code and Mistral Compute — a suite that brings frontier intelligence to end-users.\n\nWe are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited.\n\nJoin us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers.\n\nAbout the Role\n\nWe are seeking a tech-savvy Legal Tech Associate – IP & Licensing Ops to join Mistral AI’s IP and licensing team. In this role, you will be responsible for managing inbound licensing opportunities, maintaining patent and license databases, and leveraging Mistral AI tools to optimize patent operations and licensing and data partnership processes. You will work closely with the legal, product, and engineering teams to ensure efficient tracking, reporting, and support high-impact data partnership and licensing opportunities.\n\nThis role is ideal for someone who is passionate about legal tech, thrives in operational excellence, and wants to use AI to transform how IP and licensing operations are managed. If you love solving legal challenges with technology, analyzing data for strategic decisions, and driving operational excellence, this is the perfect opportunity at the intersection of law and AI.\n\nKey Responsibilities\n\nLicensing & Data Partnerships\n\n• Opportuni"},{"ref":"P13","kind":"page","title":"Account Manager - Morocco","date":"2026-06-11T03:48:28.843+00:00","date_source":null,"source_url":"https://jobs.lever.co/mistral/abff0584-d2e2-446e-b2a8-28d660e3773a","signal_url":null,"signal_json_url":null,"text":"Mistral AI - Account Manager - Morocco\n\n## Account Manager - Morocco\n\nCasablanca\n\nBusiness /\n\nFull-time /\n\nOn-site\n\napply for this job\n\nAbout Mistral\n\nAt Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.\n\nWe democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work.\n\nWe are a dynamic, collaborative team passionate about AI and its potential to transform society.\n\nOur diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited.\n\nJoin us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers.\n\nRole Summary\n\nAs part of Mistral’s expansion in North Africa, we are hiring a Senior Account Manager to lead and grow our most strategic accounts in Morocco, spanning large enterprises and public sector institutions.\n\nThis is a high-impact, senior role, focused on managing and expanding existing strategic customers with significant ACV (≥ €1M), while positioning Mistral as a long-term AI transformation partner.\n\nYou will work with major Moroccan institutions and enterprises (e.g. leading banks, industrial groups, and government bodies), owning complex, multi-year engagements where AI adoption directly supports sovereignty, operational efficiency, and business transformation.\n\nThe role is ideally based in Casablanca (for enterprise clients such as banks and industrial leaders) or Rabat (for public sector and government stakeholders).\n\nWhat you will do\n\nStrategic Account Ownership & Value-Based Selling\n\n=> Own and grow a portfolio of strategic enterprise and public sector accounts, with existing and future contracts in the €1M+ ACV range.\n\n=> Act as a trusted ad"},{"ref":"P14","kind":"page","title":"Site Reliability Engineer","date":"2026-06-11T03:48:12.830084+00:00","date_source":null,"source_url":"https://jobs.lever.co/mistral/6e16e4fa-a60b-4270-a815-06b0450fb597","signal_url":null,"signal_json_url":null,"text":"Mistral AI - Site Reliability Engineer \n\nSite Reliability Engineer\nParis / London \nEngineering & Infra /\nFull-time /\nRemote\n\napply for this job \n\nAbout Mistral \n\nAt Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life. \n\nWe democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work. \n\nWe are a dynamic, collaborative team passionate about AI and its potential to transform society. \n\nOur diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited. \n\nJoin us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers . \n\nRole Summary \n\nWe are seeking highly experienced Site Reliability Engineers (SRE) to shape the reliability, scalability and performance of our platform and customer facing applications. You will work closely with our software engineers and research teams to ensure our systems meet and exceed our internal and external customers' expectations. \n\nLocation: Remote - Europe \n\nReporting line: Team Lead, Site Reliability Engineer \n\nWhat you will do \n\nAs a Site Reliability Engineer, you balance the day-to-day operations on production systems with long-term software engineering improvements to reduce operational toil and foster the reliability, availability, and performance of these systems. \n\nOperations \n\n• Design, build, and maintain scalable, highly available and fault-tolerant infrastructures to support our web services and ML workloads \n\n• Make sure our platform, inference and model training environments are always highly available and enable seamless replication of work environments across several HPC clusters \n\n• Operate systems and troubleshoot"},{"ref":"P15","kind":"page","title":"AI Scientist - Paris/London - Onsite or Hybrid or Remote","date":"2026-06-11T03:48:12.586674+00:00","date_source":null,"source_url":"https://jobs.lever.co/mistral/675b7f06-a76b-4144-af0c-4dd3282ef489","signal_url":null,"signal_json_url":null,"text":"Mistral AI - AI Scientist - Paris/London - Onsite or Hybrid or Remote \n\nAI Scientist - Paris/London - Onsite or Hybrid or Remote\nParis\nResearch /\nFull-time /\nHybrid\n\napply for this job \n\nAbout Mistral \n\nAt Mistral we are on a mission to democratize AI, producing frontier intelligence for everyone, developed in the open, and built by engineers all over the world. \n\nWe are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation, with teams distributed between Europe, the USA and Asia. We are creative, low-ego and team-spirited. \n\nAt Mistral, we develop models for the enterprise and for consumers, focusing on delivering systems which can really change the way in which businesses operate and which can integrate into our daily lives. All while releasing frontier models open-source, for everyone to try and benefit. \n\nMistral is hiring experts in the training of large language models and distributed systems. Join us to be part of a pioneering company shaping the future of AI. \n\nWhat will you do \n\n*Research and develop novel methods to push the frontier of large language models \n\n*Work across use cases (e.g reasoning, code, agents) and modalities (e.g text, image and speech) \n\n*Build tooling and infrastructure to allow training, evaluation and analysis of AI models at scale \n\n*Work cross-functionally with other scientists, engineers and product teams to ship AI systems which have a real-world impact \n\nAbout you \n\n*You are a highly proficient software engineer in at least one programming language (Python or other, e.g. Rust, Go, Java) \n\n*You have hands-on experience with AI frameworks (e.g. PyTorch, JAX) or distributed systems (e.g. Ray, Kubernetes) \n\n*You have high engineering competence. This means being able to design complex software and make it usable in production \n\n*You are a self-starter, autonomous and a team player \n\nNow, it would be ideal if \n\n*You have hands-on experience with training large transformer models in a distributed fashion \n\n*You are able to navigate the full MLOps stack, for instance, fine-tuning, evaluation and deplo"},{"ref":"P16","kind":"page","title":"Account Executive, Enterprise, France - Paris","date":"2026-06-11T03:48:12.271957+00:00","date_source":null,"source_url":"https://jobs.lever.co/mistral/46bf0c1c-cca2-4941-bd8d-18024fa59afa","signal_url":null,"signal_json_url":null,"text":"Mistral AI - Account Executive, Enterprise, France - Paris \n\nAccount Executive, Enterprise, France - Paris\nParis\nBusiness /\nFull-time /\nHybrid\n\napply for this job \n\nAbout Mistral \n\nAt Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life. \n\nWe democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work. \n\nWe are a dynamic, collaborative team passionate about AI and its potential to transform society. \n\nOur diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited. \n\nJoin us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers . \n\nRole Summary: \n\nAs our Enterprise Sales Executive, you will be instrumental in shaping Mistral’s adoption with our largest customers across a variety of industries. You will be driving deals end2end: from prospective, first intro call until closing and beyond — together with our dedicated implementation specialist, tech and legal teams. \n\nWhat you will do: \n\nLead development (strategic outbound and qualified inbound): \n\n- Handle strategic outreach as well as warm introductions to promising enterprise customers \n\n- Converting inbound deals where upselling / more bespoke agreements can be achieved \n\nValue prop validation for customer: \n\n- Provide hands-on support and guidance to clients during a potential Proof of Concept (POC) phase, ensuring a smooth and successful evaluation process \n\n- Leverage successful POC outcomes to facilitate the conversion of POCs into long-term, revenue-generating contracts \n\nDeal management & closing: \n\n- Develop and execute strategic sales plans to convert leads into valued customers — you are th"},{"ref":"P17","kind":"page","title":"Data Scientist","date":"2026-06-11T03:48:12.246365+00:00","date_source":null,"source_url":"https://jobs.lever.co/mistral/bf5bcae2-839b-492e-a5bc-11d4427ee843","signal_url":null,"signal_json_url":null,"text":"Mistral AI - Data Scientist \n\nData Scientist\nParis\nEngineering & Infra /\nFull-time /\nOn-site\n\napply for this job \n\nAbout Mistral \n\nAt Mistral AI, we believe in the power of AI to simplify tasks, save time and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life. \n\nWe democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work. \n\nWe are a dynamic, collaborative team passionate about AI and its potential to transform society. \n\nOur diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited. \n\nJoin us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers . \n\nRole summary \n\nWe are seeking skilled and motivated Data Scientists to join our team in Paris. You will work at the intersection of product, research, and engineering . You will analyze user behavior, optimize product performance, and design data-driven features that enhance our AI product suite. This role is ideal for someone who thrives in a dynamic environment, enjoys tackling ambiguous problems, and wants to influence our product roadmap directly. The ideal candidate will have a strong background in data analysis, statistical modeling and machine learning, with a proven track record of delivering high-quality results in a fast-paced environment. If you’re passionate about data, curious about AI, and eager to shape the data science strategy and make an impact, this is the role for you. \n\nWhat you will do \n\n• Define key metrics, understand in-depth the performance of our AI products, and identify opportunities for improvement. \n\n• Design and analyze experiments (A/B tests, causal inference) to validate hypotheses and guide product decisions. \n\n• Design and implement end-to"},{"ref":"P18","kind":"page","title":"Talent Acquisition (Engineering/Product/GTM/ Science) - EMEA","date":"2026-06-11T03:48:12.19523+00:00","date_source":null,"source_url":"https://jobs.lever.co/mistral/41262cfd-5a86-4645-b059-1de4ee9b9ccb","signal_url":null,"signal_json_url":null,"text":"Mistral AI - Talent Acquisition (Engineering/Product/GTM/ Science) - EMEA \n\nTalent Acquisition (Engineering/Product/GTM/ Science) - EMEA\nParis / London / Madrid / Amsterdam / Berlin \nHR /\nFull-time /\nOn-site\n\napply for this job \n\nAbout Mistral \n\nAt Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.\n\nWe democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise as well as personal needs. Our offerings include Le Chat, La Plateforme, Mistral Code and Mistral Compute - a suite that brings frontier intelligence to end-users.\n\nWe are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited.\n\nJoin us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers.\n\nMistral AI participates in the E-Verify program \n\nBy applying, you agree to our Applicant Privacy Policy . \n\nRole Summary \n\nWe are looking for TA experts across a wide variety of functions : GTM; Corporate; Engineering/Product, Science \n\nPlease not that if you are not based in France, we would require a monthly visit to Paris after a 2 weeks onboarding in Paris \n\nWhat you will do \n\n• You’ll partner with hiring managers to find world-changing talents for Mistral \n\n• You'll be charged with finding unique candidates who bring an entrepreneurial spirit, strong commitment and passion for success \n\n• You will be responsible for guiding candidates through our hiring process and introducing them to the magic of working at Mistral \n\n• An early joiner of Mistral, you will contribute to shaping the recruitment process and our TA machinery. \n\nYour scope will be as follows: \n\nHire \n\n• Obsessed by bringing top talents \n\n• Successfully ful"},{"ref":"P19","kind":"page","title":"Open-Source Software, Machine Learning Engineer","date":"2026-06-11T03:48:11.982864+00:00","date_source":null,"source_url":"https://jobs.lever.co/mistral/ef4c26fc-3fdb-4dd2-a64e-95264ee769dd","signal_url":null,"signal_json_url":null,"text":"Mistral AI - Open-Source Software, Machine Learning Engineer \n\nOpen-Source Software, Machine Learning Engineer\nParis / London \nResearch /\nFull-time /\nHybrid\n\napply for this job \n\nAbout Mistral \n\nAt Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life. \n\nWe democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work. \n\nWe are a dynamic, collaborative team passionate about AI and its potential to transform society. \n\nOur diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited. \n\nJoin us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers . \n\nRole Summary \n\nYou will be in charge of open-sourcing state-of-the-art models, whilst maintaining and improving Mistral’s publicly available libraries. Your work is critical in helping turn research breakthroughs into tangible solutions and improve Mistral's open-source ecosystem. \n\nAbout the Open Source Software team \n\nOur OSS team is embedded in our Science team and works very closely with various engineering and marketing teams. All OSS team members can fluidly move on the production / research spectrum depending on where the needs are or where their interests lie \n\nWhat you will do \n\n• Releasing our models to open-source platforms and libraries, e.g., vLLM, GitHub, Hugging Face \n\n• Maintaining Mistral’s open-source libraries (mistral-common, mistral-finetune, mistral-inference) \n\n• Create and maintain tooling and services: both internal facing (internal research) and external facing (open-source libraries) \n\n• Implement and optimize open-source and internal libraries for performance and accuracy, ensuring p"},{"ref":"P20","kind":"page","title":"AI Scientist - Palo Alto","date":"2026-06-11T03:48:11.690289+00:00","date_source":null,"source_url":"https://jobs.lever.co/mistral/7b20d2c8-d5a7-4efd-a13e-05d920ec5985","signal_url":null,"signal_json_url":null,"text":"Mistral AI - AI Scientist - Palo Alto \n\nAI Scientist - Palo Alto\nPalo Alto\nResearch /\nFull-time /\nHybrid\n\napply for this job \n\nAbout Mistral \n\nAt Mistral we are on a mission to democratize AI, producing frontier intelligence for everyone, developed in the open, and built by engineers all over the world. \n\nWe are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation, with teams distributed between Europe, the USA and Asia. We are creative, low-ego and team-spirited. \n\nAt Mistral, we develop models for the enterprise and for consumers, focusing on delivering systems which can really change the way in which businesses operate and which can integrate into our daily lives. All while releasing frontier models open-source, for everyone to try and benefit. \n\nMistral is hiring experts in the training of large language models and distributed systems. Join us to be part of a pioneering company shaping the future of AI. \n\nWhat will you do \n\n*Research and develop novel methods to push the frontier of large language models \n\n*Work across use cases (e.g reasoning, code, agents) and modalities (e.g text, image and speech) \n\n*Build tooling and infrastructure to allow training, evaluation and analysis of AI models at scale \n\n*Work cross-functionally with other scientists, engineers and product teams to ship AI systems which have a real-world impact \n\nAbout you \n\n*You are a highly proficient software engineer in at least one programming language (Python or other, e.g. Rust, Go, Java) \n\n*You have hands-on experience with AI frameworks (e.g. PyTorch, JAX) or distributed systems (e.g. Ray, Kubernetes) \n\n*You have high engineering competence. This means being able to design complex software and make it usable in production \n\n*You are a self-starter, autonomous and a team player \n\nNow, it would be ideal if \n\n*You have hands-on experience with training large transformer models in a distributed fashion \n\n*You are able to navigate the full MLOps stack, for instance, fine-tuning, evaluation and deployment \n\n*You have a strong publication record in a relevant "},{"ref":"P21","kind":"page","title":"Applied AI, Forward Deployed Machine Learning Engineer - EMEA","date":"2026-06-11T03:48:11.628704+00:00","date_source":null,"source_url":"https://jobs.lever.co/mistral/77f6fd1b-65cf-45d8-9b68-594c62732f62","signal_url":null,"signal_json_url":null,"text":"Mistral AI - Applied AI, Forward Deployed Machine Learning Engineer - EMEA \n\nApplied AI, Forward Deployed Machine Learning Engineer - EMEA\nParis / London / Luxembourg / Marseille / Amsterdam / Munich / Lausanne \nSolutions /\nFull-time /\nOn-site\n\napply for this job \n\nAbout The Job \n\nMistral AI is seeking a Applied AI Engineer to facilitate the adoption of its products among customers and collaborate with them to address complex technical challenges. \n\nThe Applied AI team is Mistral's customer-facing technical organization. We work directly with enterprise clients from pre-sales through implementation to deploy cutting-edge AI solutions that deliver measurable business impact. \n\nOur team combines deep ML expertise with strong customer engagement skills, operating like startup CTOs who own end-to-end project execution. By joining the team you'll will bridge the gap between cutting-edge AI research and real-world enterprise applications, ensuring our solutions are robust, scalable, and aligned with both customer needs and Mistral's technological vision. \n\nWhat you will do \n\n- You’ll individually help deploy into production use cases with a considerable business impact across various industries. \n\n- You’ll work on state-of-the-art GenAI applications from consumer products to industrial use cases, driving with our customers a crucial technological transformation. \n\n- You’ll work in collaboration with our researchers, other AI engineers, product engineers on our most complex customer projects involving complex fine-tuning, state-of-the-art LLM applications, and contributing to our open-source codebases our open source codebases for tasks such as inference and fine-tuning. \n\n- You’ll be involved in pre-sales calls to understand potential clients' needs, challenges, and aspirations. You will provide technical guidance on our products and explain Mistral technologies to various stakeholders. \n\n- Your collaboration with our product and science team to improve continuously our product and model capabilities based on customers’ feedback \n\nHow We Work in Applied AI \n\n- We care about people and outputs. \n\n- What matters is what you ship, not the time you spend on it \n\n- Bureauc"},{"ref":"P22","kind":"page","title":"Research Engineer, Machine Learning - Paris/London/Zurich/Warsaw","date":"2026-06-11T03:48:11.623739+00:00","date_source":null,"source_url":"https://jobs.lever.co/mistral/07447e1d-7900-46d4-b61b-186f2f76847f","signal_url":null,"signal_json_url":null,"text":"Mistral AI - Research Engineer, Machine Learning - Paris/London/Zurich/Warsaw \n\nResearch Engineer, Machine Learning - Paris/London/Zurich/Warsaw\nParis / London / Zurich / Warsaw \nResearch /\nFull-time /\nHybrid\n\napply for this job \n\nAbout Mistral \n\nAt Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.\n\nWe democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise as well as personal needs. Our offerings include Le Chat, La Plateforme, Mistral Code and Mistral Compute - a suite that brings frontier intelligence to end-users.\n\nWe are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited.\n\nJoin us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers.\n\nMistral AI participates in the E-Verify program \n\nBy applying, you agree to our Applicant Privacy Policy . \n\nRole Summary \n\nAbout the Research Engineering team \n\nThe team spans Platform (shared infra & clean code) and Embedded (inside research squads). Engineers can move along the research↔production spectrum as needs or interests evolve.\n\nAs a Research Engineer – ML track, you’ll build and optimise the large-scale learning systems that power our open-weight models. Working hand-in-hand with Research Scientists, you’ll either join:\n\n- Platform RE Team: Enhance the shared training framework, data pipelines and cluster tooling used by every team; or\n\n- Embedded RE Team: Sit inside a research squad (Alignment, Pre-training, Multimodal, Safety …) and turn fresh ideas into repeatable, scalable code.\n\nWhat will you do \n\n• Accelerate researchers by taking on the heavy parts of large-scale ML pipelines and building robust tools.\n\n•"},{"ref":"P23","kind":"page","title":"Data Engineer","date":"2026-06-11T03:48:11.299702+00:00","date_source":null,"source_url":"https://jobs.lever.co/mistral/6f28da96-76f9-44bb-9b85-4e3519fde6d4","signal_url":null,"signal_json_url":null,"text":"Mistral AI - Data Engineer \n\nData Engineer\nParis\nEngineering & Infra /\nFull-time /\nOn-site\n\napply for this job \n\nAbout Mistral \n\nAt Mistral AI, we believe in the power of AI to simplify tasks, save time and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life. \n\nWe democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work. \n\nWe are a dynamic, collaborative team passionate about AI and its potential to transform society. \n\nOur diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited. \n\nJoin us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers . \n\nRole summary \n\nWe are seeking passionate and talented Data Engineers to join our team. Candidates with an Analytics Engineering background are also encouraged to apply. \n\nIn this role, you will have the unique opportunity to build, optimize, and maintain our data infrastructure. You will work with large volumes of data, enabling product teams to access secure and reliable data quickly. Your contributions will support our science team in enhancing the quality of our state-of-the-art AI models and help business users make informed decisions. \n\nWhat you will do \n\n• Design, build, and maintain scalable data pipelines, ETL processes, and analytics infrastructure. Automate data quality checks and validation processes. \n\n• Collaborate with cross-functional teams to understand data needs and deliver high-quality, actionable solutions, eg work closely with machine learning teams to support model training, deployment pipelines, and feature stores. \n\n• Optimize data storage, retrieval, processing, and queries for performance, scalability, and cost-efficiency. \n\n• Define and enforce data "},{"ref":"P24","kind":"page","title":"Lead Software Engineer in Test, QA","date":"2026-06-11T03:48:11.171363+00:00","date_source":null,"source_url":"https://jobs.lever.co/mistral/03918386-cb56-4e4d-afa8-1f8b7676a4a6","signal_url":null,"signal_json_url":null,"text":"Mistral AI - Lead Software Engineer in Test, QA \n\nLead Software Engineer in Test, QA\nParis\nEngineering & Infra /\nFull-time /\nHybrid\n\napply for this job \n\nAbout Mistral \n\nAt Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life. \n\nWe democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work. \n\nWe are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited. \n\nJoin us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers . \n\nRole summary \n\nWe are seeking a skilled and proactive QA Engineer to join our team and ensure the reliability, accuracy, and robustness of our AI-powered products. In this role, you will design and execute test strategies for our applications, APIs and machine learning models. Your work will involve automated testing, edge-case analysis, and collaboration with cross-functional teams to deliver seamless, high-quality user experiences. If you thrive in a dynamic environment and are passionate about quality in AI systems, this is a perfect opportunity to make a tangible impact. \n\nWhat you will do \n\nTest Automation: Develop automated test suites to validate app features, APIs, and model integrations, ensuring end-to-end reliability and user experience. \n\nEdge Case Analysis: Collaborate with PMs and other stakeholders to identify and rigorously test edge cases, improving the robustness of both platform features and models. \n\nQuality Platform Development: Contribute to building tools and frameworks that enable more efficient and scalable quali"},{"ref":"P25","kind":"page","title":"AI Deployment Strategist - Munich, Germany","date":"2026-06-11T03:48:11.06161+00:00","date_source":null,"source_url":"https://jobs.lever.co/mistral/1937a5af-2c9b-4a75-bb91-b06ebe714dbd","signal_url":null,"signal_json_url":null,"text":"Mistral AI - AI Deployment Strategist - Munich, Germany \n\nAI Deployment Strategist - Munich, Germany\nMunich\nSolutions /\nFull-time /\nOn-site\n\napply for this job \n\nAbout Mistral \n\nAt Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life. \n\nWe democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work. \n\nWe are a dynamic, collaborative team passionate about AI and its potential to transform society. \n\nOur diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited. \n\nJoin us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers .\n\nRole Summary : AI Deployment Strategist \n\nAs an AI Deployment Strategist , you will drive the adoption and deployment of Mistral’s AI solutions, working closely with customers from strategic vision to production implementation. This role sits at the intersection of business strategy, AI innovation, and hands-on deployment, ensuring our customers achieve transformative outcomes. \n\nYou will partner with senior executives to design AI roadmaps, collaborate with the Applied AI team to deliver solutions in production, and ensure seamless transitions from presales to postsales. Your work will directly contribute to customer success, bridging the gap between strategy and execution. \n\nThis role is ideal for those who thrive in a fast-paced environment, enjoy solving complex business challenges, and are passionate about turning AI potential into real-world impact. \n\nWhat you will do \n\nStrategic Discovery & Vision Setting \n\n• Lead executive-level workshops to identify business challenges and opportunities where Mistral’s AI can drive step"},{"ref":"P26","kind":"page","title":"Technical Program Manager, Engineering","date":"2026-06-11T03:48:11.02379+00:00","date_source":null,"source_url":"https://jobs.lever.co/mistral/a1854159-922e-4de7-adb6-7c1b608c147f","signal_url":null,"signal_json_url":null,"text":"Mistral AI - Technical Program Manager, Engineering \n\nTechnical Program Manager, Engineering\nParis\nEngineering & Infra /\nFull-time /\nHybrid\n\napply for this job \n\nAbout Mistral \n\nAt Mistral AI, we believe in the power of AI to simplify tasks, save time and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life. \n\nWe democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work. \n\nWe are a dynamic, collaborative team passionate about AI and its potential to transform society. \n\nOur diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited. \n\nJoin us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers . \n\nRole summary \n\nWe are seeking experienced and highly motivated Technical Program Managers (TPMs) to join our Engineering organization and drive the delivery of high-impact technical projects. In this role, you will plan, execute, and oversee complex programs aligned with our strategic goals. Success requires a combination of technical expertise, project management excellence, hands-on engagement, and strong cross-functional leadership to ensure projects are delivered on time, within budget, and to the highest standards.\n\nThe TPM role spans multiple critical areas of program management:\n\nFunctional/Technical Support – Collaborate with teams to refine and communicate roadmaps, organize delivery, maintain project tracking tools, identify dependencies, and proactively track blockers. Work closely with Product Managers to escalate risks and ensure alignment.\n\nEngineering Operations – Drive efficiency by automating processes and championing their adoption across Engineering teams, reducing manual effort and enabling scalable, consiste"},{"ref":"P27","kind":"page","title":"Senior/Staff Applied Scientist/Research Engineer - EMEA","date":"2026-06-11T03:48:10.849391+00:00","date_source":null,"source_url":"https://jobs.lever.co/mistral/b7ae8fc4-5779-4ad2-8f5b-632b4d9498cf","signal_url":null,"signal_json_url":null,"text":"Mistral AI - Senior/Staff Applied Scientist/Research Engineer - EMEA \n\nSenior/Staff Applied Scientist/Research Engineer - EMEA\nParis / London \nSolutions /\nFull-time /\nHybrid\n\napply for this job \n\nAbout Mistral \n\nAt Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.\n\nWe democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work.\n\nWe are a dynamic, collaborative team passionate about AI and its potential to transform society.\n\nOur diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited.\n\nJoin us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers.\n\nAbout The Job \n\nMistral AI is seeking Applied Scientists and Research Engineers to drive innovative research and collaborate with clients on complex research projects.\n\nYou will develop SOTA models across different modalities such as text, image, and speech. By developing novel methods and research ideas you will apply these models across a diverse set of use cases and domains. Working cross-functionally with both external and internal science, engineering, and product teams you will deliver high-impact AI solutions that turn the needle.\n\nWhat you will do \n\n• Run pre-training, post-training and deploy state of the art models on clusters with thousands of GPUs. You don’t panic when you see OOM errors or when NCCL feels like not wanting to talk.\n\n• Generate and curate data for pre-training and post-training, working on evaluations and making sure the model’s performance beats expectations.\n\n• Develop the necessary tools and frameworks to facilitate data generation, model training, evaluation and deploy"},{"ref":"P28","kind":"page","title":"Applied AI Engineer, ML Infrastructure Engineer / Devops - EMEA","date":"2026-06-11T03:48:10.755018+00:00","date_source":null,"source_url":"https://jobs.lever.co/mistral/3e51d533-1f2d-48e3-9a2b-33fc7e8b0c0c","signal_url":null,"signal_json_url":null,"text":"Mistral AI - Applied AI Engineer, ML Infrastructure Engineer / Devops - EMEA \n\nApplied AI Engineer, ML Infrastructure Engineer / Devops - EMEA\nParis / London / Marseille / Luxembourg / Lausanne \nSolutions /\nFull-time /\nOn-site\n\napply for this job \n\nAbout Mistral \n\nAt Mistral AI, we believe in the power of AI to simplify tasks, save time, and enhance learning and creativity. Our technology is designed to integrate seamlessly into daily working life.\n\nWe democratize AI through high-performance, optimized, open-source and cutting-edge models, products and solutions. Our comprehensive AI platform is designed to meet enterprise needs, whether on-premises or in cloud environments. Our offerings include le Chat, the AI assistant for life and work.\n\nWe are a dynamic, collaborative team passionate about AI and its potential to transform society.\n\nOur diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between France, USA, UK, Germany and Singapore. We are creative, low-ego and team-spirited.\n\nJoin us to be part of a pioneering company shaping the future of AI. Together, we can make a meaningful impact. See more about our culture on https://mistral.ai/careers .\n\nAbout The Job \n\nMistral AI is seeking an Applied AI Engineer focused on DevOps to facilitate the adoption of its products among customers and collaborate with them to address complex technical challenges.\n\nApplied AI Engineers, ML Infra at Mistral AI work directly with customers to quickly understand their greatest challenges and design and implement AI solutions. In this role, you’ll apply your problem-solving ability, creativity, and technical skills to help organizations use AI to drive real impact in the world. You’ll have the opportunity to gain rare insight into and contribute to some of the most important industries and institutions globally!\n\nApplied AI Engineers, ML Infra responsibilities look similar to those of a startup CTO: you’ll work in small teams and own end-to-end execution of high-stakes projects. 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v1.7.3 · signal_desk=releases · occurred_at=2026-06-08T09:05:18+00:00 · url=https://github.com/mistralai/workflows-starter-app/releases/tag/v1.7.3 · raw={\"repo\":\"mistralai/workflows-starter-app\"}"},{"ref":"E13","kind":"event","title":"Account Executive, CyberSecurity","date":"2026-06-08T08:29:36.333+00:00","date_source":"lever.createdAt","source_url":"https://jobs.lever.co/mistral/66ade4de-d49e-434f-9285-5e8d460b1bca","signal_url":"https://onlylabs.fyi/signals/d57856a9-ba37-43de-9c28-b54595e5f23d","signal_json_url":"https://onlylabs.fyi/signals/d57856a9-ba37-43de-9c28-b54595e5f23d/signal.json","text":"job_opened · Account Executive, CyberSecurity · signal_desk=hiring · occurred_at=2026-06-08T08:29:36.333+00:00 · url=https://jobs.lever.co/mistral/66ade4de-d49e-434f-9285-5e8d460b1bca · data_radar_lanes=Safety and policy · data_radar_terms=security · data_radar_reason=Mistral AI has a job signal matching safety and policy. · raw={\"location\":\"Paris\",\"team\":\"Business\",\"ats\":\"lever\"}"},{"ref":"E14","kind":"event","title":"Applied AI Engineer, CyberSecurity","date":"2026-06-08T08:24:02.651+00:00","date_source":"lever.createdAt","source_url":"https://jobs.lever.co/mistral/98e6a2ea-7049-4c8d-88b7-c9d824eea6f1","signal_url":"https://onlylabs.fyi/signals/325b4c91-c353-4bfd-9325-a33bb40b43a2","signal_json_url":"https://onlylabs.fyi/signals/325b4c91-c353-4bfd-9325-a33bb40b43a2/signal.json","text":"job_opened · Applied AI Engineer, CyberSecurity · signal_desk=hiring · occurred_at=2026-06-08T08:24:02.651+00:00 · url=https://jobs.lever.co/mistral/98e6a2ea-7049-4c8d-88b7-c9d824eea6f1 · data_radar_lanes=Safety and policy, Product and customer · data_radar_terms=security, solutions · data_radar_reason=Mistral AI has a job signal matching safety and policy, product and customer. · raw={\"location\":\"Paris\",\"team\":\"Solutions\",\"ats\":\"lever\"}"},{"ref":"E15","kind":"event","title":"Pentester, Offensive 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raw={\"location\":\"Paris\",\"team\":\"Solutions\",\"ats\":\"lever\"}"},{"ref":"E16","kind":"event","title":"mistralai/Mistral-Large-3-675B-Base-2512","date":"2025-11-30T13:05:40+00:00","date_source":"source","source_url":"https://huggingface.co/mistralai/Mistral-Large-3-675B-Base-2512","signal_url":"https://onlylabs.fyi/signals/3cd80374-5367-4242-a9c3-0858f6060b92","signal_json_url":"https://onlylabs.fyi/signals/3cd80374-5367-4242-a9c3-0858f6060b92/signal.json","text":"model_released · mistralai/Mistral-Large-3-675B-Base-2512 · signal_desk=releases · occurred_at=2025-11-30T13:05:40+00:00 · url=https://huggingface.co/mistralai/Mistral-Large-3-675B-Base-2512 · hf_downloads=23 · hf_likes=43 · license=apache-2.0"},{"ref":"E17","kind":"event","title":"Workplace Operations Manager","date":"2026-06-05T13:09:00.162+00:00","date_source":"lever.createdAt","source_url":"https://jobs.lever.co/mistral/2c55ac3a-50f8-45bd-b2d3-05b2caedc1dc","signal_url":"https://onlylabs.fyi/signals/8339a5c8-7199-404d-852a-07ec9e7d41df","signal_json_url":"https://onlylabs.fyi/signals/8339a5c8-7199-404d-852a-07ec9e7d41df/signal.json","text":"job_opened · Workplace Operations Manager · signal_desk=hiring · occurred_at=2026-06-05T13:09:00.162+00:00 · url=https://jobs.lever.co/mistral/2c55ac3a-50f8-45bd-b2d3-05b2caedc1dc · raw={\"location\":\"Paris\",\"team\":\"HR\",\"ats\":\"lever\"}"},{"ref":"E18","kind":"event","title":"mistralai/mistral-vibe v2.14.0","date":"2026-06-04T16:27:54+00:00","date_source":"source","source_url":"https://github.com/mistralai/mistral-vibe/releases/tag/v2.14.0","signal_url":"https://onlylabs.fyi/signals/2f6602b5-392a-484e-90e7-02f61817c54a","signal_json_url":"https://onlylabs.fyi/signals/2f6602b5-392a-484e-90e7-02f61817c54a/signal.json","text":"release · mistralai/mistral-vibe v2.14.0 · signal_desk=releases · occurred_at=2026-06-04T16:27:54+00:00 · url=https://github.com/mistralai/mistral-vibe/releases/tag/v2.14.0 · raw={\"repo\":\"mistralai/mistral-vibe\"}"},{"ref":"E19","kind":"event","title":"Strategic Account Marketing Manager, APAC","date":"2026-06-04T16:05:30.277+00:00","date_source":"lever.createdAt","source_url":"https://jobs.lever.co/mistral/7298430f-9608-4e46-82c1-d72daa963fe6","signal_url":"https://onlylabs.fyi/signals/192ffb99-8ca9-46b3-948f-14645c6139ce","signal_json_url":"https://onlylabs.fyi/signals/192ffb99-8ca9-46b3-948f-14645c6139ce/signal.json","text":"job_opened · Strategic Account Marketing Manager, APAC · signal_desk=hiring · occurred_at=2026-06-04T16:05:30.277+00:00 · url=https://jobs.lever.co/mistral/7298430f-9608-4e46-82c1-d72daa963fe6 · raw={\"location\":\"Singapore\",\"team\":\"Marketing\",\"ats\":\"lever\"}"},{"ref":"E20","kind":"event","title":"mistralai/mistral-common 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signal_desk=releases · occurred_at=2026-06-03T14:51:40+00:00 · url=https://github.com/mistralai/mistral-common/releases/tag/v1.11.2 · raw={\"repo\":\"mistralai/mistral-common\"}"},{"ref":"E22","kind":"event","title":"mistralai/client-python v2.4.9","date":"2026-06-03T13:04:25+00:00","date_source":"source","source_url":"https://github.com/mistralai/client-python/releases/tag/v2.4.9","signal_url":"https://onlylabs.fyi/signals/d6ec7dc1-0148-4ce4-8aa7-0669fe359fbe","signal_json_url":"https://onlylabs.fyi/signals/d6ec7dc1-0148-4ce4-8aa7-0669fe359fbe/signal.json","text":"release · mistralai/client-python v2.4.9 · signal_desk=releases · occurred_at=2026-06-03T13:04:25+00:00 · url=https://github.com/mistralai/client-python/releases/tag/v2.4.9 · raw={\"repo\":\"mistralai/client-python\"}"},{"ref":"E23","kind":"event","title":"Workplace Project Manager - Paris","date":"2026-06-03T12:00:56.83+00:00","date_source":"lever.createdAt","source_url":"https://jobs.lever.co/mistral/71e85101-8cba-4e65-8bd1-48414d4bcfc0","signal_url":"https://onlylabs.fyi/signals/630f7bac-c320-4b49-994f-20ece218171d","signal_json_url":"https://onlylabs.fyi/signals/630f7bac-c320-4b49-994f-20ece218171d/signal.json","text":"job_opened · Workplace Project Manager - Paris · signal_desk=hiring · occurred_at=2026-06-03T12:00:56.83+00:00 · url=https://jobs.lever.co/mistral/71e85101-8cba-4e65-8bd1-48414d4bcfc0 · raw={\"location\":\"Paris\",\"team\":\"HR\",\"ats\":\"lever\"}"},{"ref":"E24","kind":"event","title":"Group Financial 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France","date":"2026-06-02T15:02:52.658+00:00","date_source":"lever.createdAt","source_url":"https://jobs.lever.co/mistral/03863192-718a-45f9-9c43-bb053d085543","signal_url":"https://onlylabs.fyi/signals/23a33701-91b5-43ac-a96b-204a8c5e2317","signal_json_url":"https://onlylabs.fyi/signals/23a33701-91b5-43ac-a96b-204a8c5e2317/signal.json","text":"job_opened · HR People Ops France · signal_desk=hiring · occurred_at=2026-06-02T15:02:52.658+00:00 · url=https://jobs.lever.co/mistral/03863192-718a-45f9-9c43-bb053d085543 · raw={\"location\":\"Paris\",\"team\":\"HR\",\"ats\":\"lever\"}"},{"ref":"E30","kind":"event","title":"Applied Scientist / Domain Expert, AI4Engineering - 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AI, Use-case, Software Engineer (Harness) · signal_desk=hiring · occurred_at=2026-05-28T11:49:46.8+00:00 · url=https://jobs.lever.co/mistral/49aa2bb7-5504-46d3-bc40-e1bcdb12cee2 · data_radar_lanes=Product and customer · data_radar_terms=solutions · data_radar_reason=Mistral AI has a job signal matching product and customer. · raw={\"location\":\"Paris\",\"team\":\"Solutions\",\"ats\":\"lever\"}"},{"ref":"E35","kind":"event","title":"mistralai/client-python v2.4.8","date":"2026-05-28T10:00:48+00:00","date_source":"source","source_url":"https://github.com/mistralai/client-python/releases/tag/v2.4.8","signal_url":"https://onlylabs.fyi/signals/e7b11ccc-328f-4f83-9a1a-7cfad46d60aa","signal_json_url":"https://onlylabs.fyi/signals/e7b11ccc-328f-4f83-9a1a-7cfad46d60aa/signal.json","text":"release · mistralai/client-python v2.4.8 · signal_desk=releases · occurred_at=2026-05-28T10:00:48+00:00 · url=https://github.com/mistralai/client-python/releases/tag/v2.4.8 · 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mistralai/client-ts packages/mistralai-gcp/v2.0.0 · signal_desk=releases · occurred_at=2026-05-27T17:08:09+00:00 · url=https://github.com/mistralai/client-ts/releases/tag/packages/mistralai-gcp/v2.0.0 · raw={\"repo\":\"mistralai/client-ts\"}"},{"ref":"E39","kind":"event","title":"mistralai/client-ts packages/mistralai-azure/v2.0.0","date":"2026-05-27T17:07:46+00:00","date_source":"source","source_url":"https://github.com/mistralai/client-ts/releases/tag/packages/mistralai-azure/v2.0.0","signal_url":"https://onlylabs.fyi/signals/b6924738-6b04-4bff-ae46-e65d2cfd594b","signal_json_url":"https://onlylabs.fyi/signals/b6924738-6b04-4bff-ae46-e65d2cfd594b/signal.json","text":"release · mistralai/client-ts packages/mistralai-azure/v2.0.0 · signal_desk=releases · occurred_at=2026-05-27T17:07:46+00:00 · url=https://github.com/mistralai/client-ts/releases/tag/packages/mistralai-azure/v2.0.0 · raw={\"repo\":\"mistralai/client-ts\"}"},{"ref":"E40","kind":"event","title":"mistralai/client-ts 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AI4Engineering - EMEA · signal_desk=hiring · occurred_at=2026-05-27T15:43:12.99+00:00 · url=https://jobs.lever.co/mistral/bfcc2d05-141a-49d3-aa4d-20d743ede9d9 · data_radar_lanes=Product and customer · data_radar_terms=solutions, deployment · data_radar_reason=Mistral AI has a job signal matching product and customer. · raw={\"location\":\"Paris\",\"team\":\"Solutions\",\"ats\":\"lever\"}"},{"ref":"E42","kind":"event","title":"mistralai/mistral-vibe v2.11.1","date":"2026-05-27T15:11:47+00:00","date_source":"source","source_url":"https://github.com/mistralai/mistral-vibe/releases/tag/v2.11.1","signal_url":"https://onlylabs.fyi/signals/c76147a0-742b-406d-bfdc-55b9409a0eae","signal_json_url":"https://onlylabs.fyi/signals/c76147a0-742b-406d-bfdc-55b9409a0eae/signal.json","text":"release · mistralai/mistral-vibe v2.11.1 · signal_desk=releases · occurred_at=2026-05-27T15:11:47+00:00 · url=https://github.com/mistralai/mistral-vibe/releases/tag/v2.11.1 · 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mistralai/workflows-starter-app v1.7.0 · signal_desk=releases · occurred_at=2026-05-19T13:30:42+00:00 · url=https://github.com/mistralai/workflows-starter-app/releases/tag/v1.7.0 · raw={\"repo\":\"mistralai/workflows-starter-app\"}"},{"ref":"E56","kind":"event","title":"AI Deployment Strategist, MINDEF - Singapore","date":"2026-05-12T10:01:52.061+00:00","date_source":"lever.createdAt","source_url":"https://jobs.lever.co/mistral/3ec6fd88-fc86-4c2c-bb5d-0c66876ba62d","signal_url":"https://onlylabs.fyi/signals/d4d2362a-54be-4fd3-893a-de520f8fad5c","signal_json_url":"https://onlylabs.fyi/signals/d4d2362a-54be-4fd3-893a-de520f8fad5c/signal.json","text":"job_opened · AI Deployment Strategist, MINDEF - Singapore · signal_desk=hiring · occurred_at=2026-05-12T10:01:52.061+00:00 · url=https://jobs.lever.co/mistral/3ec6fd88-fc86-4c2c-bb5d-0c66876ba62d · data_radar_lanes=Product and customer · data_radar_terms=solutions, deployment · data_radar_reason=Mistral AI has a job signal matching product 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