{"schema_version":"onlylabs.public_analysis.v1","url":"https://onlylabs.fyi/analysis/qwen","json_url":"https://onlylabs.fyi/analysis/qwen/analysis.json","evidence_json_url":"https://onlylabs.fyi/analysis/qwen/evidence.json","generated_at":"2026-06-11T18:04:21.313Z","analysis":{"org_slug":"qwen","url":"https://onlylabs.fyi/analysis/qwen","json_url":"https://onlylabs.fyi/analysis/qwen/analysis.json","evidence_json_url":"https://onlylabs.fyi/analysis/qwen/evidence.json","dossier_url":"https://onlylabs.fyi/labs/qwen","org":{"slug":"qwen","name":"Qwen (Alibaba Cloud)","category":"frontier-lab","category_label":"Frontier lab","homepage_url":"https://qwen.ai/"},"title":"Qwen (Alibaba Cloud) analysis","summary":"Qwen (Alibaba Cloud) is running one of the most prolific open-weight release cadences in the field, shipping a full ladder of dense and Mixture-of-Experts models — currently the Qwen3.5 and Qwen3.6 generations — across every modality and a parallel agentic coding stack (qwen-code, 25k stars). Adoption is enormous: its current flagship-tier checkpoints each pull millions of Hugging Face downloads in a 30-day window.…","markdown":"## Thesis\n\nQwen (Alibaba Cloud) is running one of the most prolific open-weight release cadences in the field, shipping a full ladder of dense and Mixture-of-Experts models — currently the **Qwen3.5** and **Qwen3.6** generations — across every modality and a parallel **agentic coding** stack ([qwen-code](https://github.com/QwenLM/qwen-code), 25k stars). Adoption is enormous: its current flagship-tier checkpoints each pull millions of Hugging Face downloads in a 30-day window. The lab pairs frontier-scale MoE models (up to **Qwen3.5-397B-A17B**) with a dense small-model line tuned for production and mobile, and backs both with a steady stream of first-party research writing.\n\n## Shipping\n\nAcross modalities, the most-downloaded checkpoints in the context are the small dense **Qwen3.5** instruct models: [Qwen/Qwen3.5-4B](https://huggingface.co/Qwen/Qwen3.5-4B) at **9,934,423** 30-day downloads (614 likes) and [Qwen/Qwen3.5-9B](https://huggingface.co/Qwen/Qwen3.5-9B) at **9,277,612** (1,536 likes). The new **Qwen3.6** generation is already pulling heavy traffic — [Qwen/Qwen3.6-35B-A3B](https://huggingface.co/Qwen/Qwen3.6-35B-A3B) (MoE) at **5,852,936** downloads / 2,038 likes and [Qwen/Qwen3.6-27B](https://huggingface.co/Qwen/Qwen3.6-27B) at **5,541,236** / 1,638 likes.\n\nThe MoE strategy spans sizes: the flagship [Qwen3.5-397B-A17B](https://huggingface.co/Qwen/Qwen3.5-397B-A17B) (403B params, 17B active; 1,077,681 downloads, 1,504 likes), [Qwen3.5-122B-A10B](https://huggingface.co/Qwen/Qwen3.5-122B-A10B) (815,955), and [Qwen3.5-35B-A3B](https://huggingface.co/Qwen/Qwen3.5-35B-A3B) (2,754,795). A dense ladder fills out production and edge use: [Qwen3.5-27B](https://huggingface.co/Qwen/Qwen3.5-27B) (2,857,230), [Qwen3.5-2B](https://huggingface.co/Qwen/Qwen3.5-2B) (1,841,841), and [Qwen3.5-0.8B](https://huggingface.co/Qwen/Qwen3.5-0.8B) (2,657,382). Matching `-Base` variants ship for most sizes (e.g. [Qwen3.5-4B-Base](https://huggingface.co/Qwen/Qwen3.5-4B-Base), 205,712 downloads), confirming the standard base-plus-instruct release pattern.\n\nOn GitHub, the lab's top repos are [QwenLM/Qwen3](https://github.com/QwenLM/Qwen3) (**27,290** stars), [QwenLM/qwen-code](https://github.com/QwenLM/qwen-code) (**25,009**), [QwenLM/Qwen](https://github.com/QwenLM/Qwen) (**21,255**), and the multimodal/coding lines [QwenLM/Qwen3-VL](https://github.com/QwenLM/Qwen3-VL) (**19,329**), [QwenLM/Qwen3-Coder](https://github.com/QwenLM/Qwen3-Coder) (**16,601**), and [QwenLM/Qwen-Agent](https://github.com/QwenLM/Qwen-Agent) (**16,491**). Speech and image are active too: [Qwen3-TTS](https://github.com/QwenLM/Qwen3-TTS) (11,800), [Qwen-Image](https://github.com/QwenLM/Qwen-Image) (7,977), and [Qwen3-Omni](https://github.com/QwenLM/Qwen3-Omni) (3,819). Release activity is concentrated in the **qwen-code** agentic CLI, which is on a near-daily nightly cadence — the latest tagged builds run from [v0.17.1](https://github.com/QwenLM/qwen-code/releases/tag/v0.17.1) through nightlies dated 20260604–20260608 — alongside supporting repos [qwen-code-examples v0.1](https://github.com/QwenLM/qwen-code-examples/releases/tag/v0.1) and [qwen-code-action v0.1.1](https://github.com/QwenLM/qwen-code-action/releases/tag/v0.1.1).\n\n## Research themes\n\nQwen's first-party writing traces a consistent arc from early unified multimodal pretraining to today's reasoning and agentic systems:\n\n- **Generalist / unified multimodal models** — the lab's roots: [OFA: Towards Building a One-For-All Model](https://qwenlm.github.io/blog/ofa/), [OFASys: Enabling Multitask Learning with One Line of Code](https://qwenlm.github.io/blog/ofasys/), and [Chinese CLIP](https://qwenlm.github.io/blog/chinese-clip/).\n- **Foundation-model generations** — [Introducing Qwen](https://qwenlm.github.io/blog/qwen/), [Introducing Qwen1.5](https://qwenlm.github.io/blog/qwen1.5/), [Hello Qwen2](https://qwenlm.github.io/blog/qwen2/), and [Qwen2.5: A Party of Foundation Models](https://qwenlm.github.io/blog/qwen2.5/).\n- **Mixture-of-Experts efficiency** — [Qwen1.5-MoE: Matching 7B Model Performance with 1/3 Activated Parameters](https://qwenlm.github.io/blog/qwen-moe/), the through-line behind today's A3B/A10B/A17B releases.\n- **Long context** — [Generalizing an LLM from 8k to 1M Context using Qwen-Agent](https://qwenlm.github.io/blog/qwen-agent-2405/) and [Extending the Context Length to 1M Tokens!](https://qwenlm.github.io/blog/qwen2.5-turbo/).\n- **Math & reasoning** — [Introducing Qwen2-Math](https://qwenlm.github.io/blog/qwen2-math/), [Qwen2.5-Math](https://qwenlm.github.io/blog/qwen2.5-math/), [Towards Effective Process Supervision in Mathematical Reasoning](https://qwenlm.github.io/blog/qwen2.5-math-prm/), and the reasoning-first [QwQ: Reflect Deeply on the Boundaries of the Unknown](https://qwenlm.github.io/blog/qwq-32b-preview/) plus its visual counterpart [QVQ: To See the World with Wisdom](https://qwenlm.github.io/blog/qvq-72b-preview/).\n- **Code** — [Code with CodeQwen1.5](https://qwenlm.github.io/blog/codeqwen1.5/) and [Qwen2.5-Coder: Code More, Learn More!](https://qwenlm.github.io/blog/qwen2.5-coder/), where the [Coder family post](https://qwenlm.github.io/blog/qwen2.5-coder-family/) positions Qwen2.5-Coder-32B-Instruct as a SOTA open code model \"matching the coding capabilities of GPT-4o.\"\n- **Audio & vision modalities** — [Qwen-VL](https://qwenlm.github.io/blog/qwen-vl/), [Qwen2-VL: To See the World More Clearly](https://qwenlm.github.io/blog/qwen2-vl/), and [Qwen2-Audio: Chat with Your Voice!](https://qwenlm.github.io/blog/qwen2-audio/).\n\n## Hiring & scaling\n\nThe captured roles are all on the **通义大模型事业部** (Tongyi large-model division), based in **杭州 (Hangzhou)**: algorithm engineer (算法工程师), R&D engineer (研发工程师), and their senior counterparts (高级算法工程师 / 高级研发工程师). The split between algorithm and engineering tracks — each at both standard and senior levels — signals continued investment in both core model research and the production/infra stack behind it, concentrated in a single Hangzhou hub rather than distributed teams.\n\n## Traction highlights\n\n- **Hacker News:** the standout thread is [QwenLM/Qwen3-Omni](https://github.com/QwenLM/Qwen3-Omni) at **571 points / 142 comments**, far ahead of the next — [QwenLM/Qwen](https://github.com/QwenLM/Qwen) (36 points, 51 comments) and [QwenLM/Qwen3-VL-Embedding](https://github.com/QwenLM/Qwen3-VL-Embedding) (11 points). Multimodal/omni work draws the strongest external attention.\n- **Most-starred repos:** [QwenLM/Qwen3](https://github.com/QwenLM/Qwen3) (27,290) and [QwenLM/qwen-code](https://github.com/QwenLM/qwen-code) (25,009) lead, with [Qwen3-VL](https://github.com/QwenLM/Qwen3-VL) (19,329) and [Qwen3-Coder](https://github.com/QwenLM/Qwen3-Coder) (16,601) close behind.\n- **Most-downloaded models:** [Qwen3.5-4B](https://huggingface.co/Qwen/Qwen3.5-4B) (9.93M) and [Qwen3.5-9B](https://huggingface.co/Qwen/Qwen3.5-9B) (9.28M) dominate 30-day downloads — small dense models carry the bulk of real-world usage, while the 397B-A17B flagship still clears 1M.\n\n## Sources\n\n- Homepage: https://qwen.ai/\n- [Qwen/Qwen3.5-4B](https://huggingface.co/Qwen/Qwen3.5-4B) · [Qwen/Qwen3.5-9B](https://huggingface.co/Qwen/Qwen3.5-9B) · [Qwen/Qwen3.6-35B-A3B](https://huggingface.co/Qwen/Qwen3.6-35B-A3B) · [Qwen/Qwen3.6-27B](https://huggingface.co/Qwen/Qwen3.6-27B) · [Qwen/Qwen3.5-397B-A17B](https://huggingface.co/Qwen/Qwen3.5-397B-A17B) · [Qwen/Qwen3.5-122B-A10B](https://huggingface.co/Qwen/Qwen3.5-122B-A10B)\n- [QwenLM/Qwen3](https://github.com/QwenLM/Qwen3) · [QwenLM/qwen-code](https://github.com/QwenLM/qwen-code) · [QwenLM/Qwen3-VL](https://github.com/QwenLM/Qwen3-VL) · [QwenLM/Qwen3-Coder](https://github.com/QwenLM/Qwen3-Coder) · [QwenLM/Qwen-Agent](https://github.com/QwenLM/Qwen-Agent) · [QwenLM/Qwen3-Omni](https://github.com/QwenLM/Qwen3-Omni)\n- qwen-code releases: [v0.17.1](https://github.com/QwenLM/qwen-code/releases/tag/v0.17.1) · [qwen-code-action v0.1.1](https://github.com/QwenLM/qwen-code-action/releases/tag/v0.1.1)\n- Blog: [Qwen2.5](https://qwenlm.github.io/blog/qwen2.5/) · [Qwen1.5-MoE](https://qwenlm.github.io/blog/qwen-moe/) · [Extending Context to 1M Tokens](https://qwenlm.github.io/blog/qwen2.5-turbo/) · [QwQ](https://qwenlm.github.io/blog/qwq-32b-preview/) · [Qwen2.5-Coder](https://qwenlm.github.io/blog/qwen2.5-coder/) · [Qwen2-VL](https://qwenlm.github.io/blog/qwen2-vl/)","generated_at":"2026-06-08T15:59:09.823+00:00","citations":[{"url":"https://github.com/QwenLM/qwen-code","path":null,"label":"QwenLM/qwen-code","type":"external"},{"url":"https://huggingface.co/Qwen/Qwen3.5-4B","path":null,"label":"Qwen/Qwen3.5-4B","type":"external"},{"url":"https://huggingface.co/Qwen/Qwen3.5-9B","path":null,"label":"Qwen/Qwen3.5-9B","type":"external"},{"url":"https://huggingface.co/Qwen/Qwen3.6-35B-A3B","path":null,"label":"Qwen/Qwen3.6-35B-A3B","type":"external"},{"url":"https://huggingface.co/Qwen/Qwen3.6-27B","path":null,"label":"Qwen/Qwen3.6-27B","type":"external"},{"url":"https://huggingface.co/Qwen/Qwen3.5-397B-A17B","path":null,"label":"Qwen/Qwen3.5-397B-A17B","type":"external"},{"url":"https://huggingface.co/Qwen/Qwen3.5-122B-A10B","path":null,"label":"Qwen/Qwen3.5-122B-A10B","type":"external"},{"url":"https://huggingface.co/Qwen/Qwen3.5-35B-A3B","path":null,"label":"Qwen/Qwen3.5-35B-A3B","type":"external"},{"url":"https://huggingface.co/Qwen/Qwen3.5-27B","path":null,"label":"Qwen/Qwen3.5-27B","type":"external"},{"url":"https://huggingface.co/Qwen/Qwen3.5-2B","path":null,"label":"Qwen/Qwen3.5-2B","type":"external"},{"url":"https://huggingface.co/Qwen/Qwen3.5-0.8B","path":null,"label":"Qwen/Qwen3.5-0.8B","type":"external"},{"url":"https://huggingface.co/Qwen/Qwen3.5-4B-Base","path":null,"label":"Qwen/Qwen3.5-4B-Base","type":"external"},{"url":"https://github.com/QwenLM/Qwen3","path":null,"label":"QwenLM/Qwen3","type":"external"},{"url":"https://github.com/QwenLM/Qwen","path":null,"label":"QwenLM/Qwen","type":"external"},{"url":"https://github.com/QwenLM/Qwen3-VL","path":null,"label":"QwenLM/Qwen3-VL","type":"external"},{"url":"https://github.com/QwenLM/Qwen3-Coder","path":null,"label":"QwenLM/Qwen3-Coder","type":"external"},{"url":"https://github.com/QwenLM/Qwen-Agent","path":null,"label":"QwenLM/Qwen-Agent","type":"external"},{"url":"https://github.com/QwenLM/Qwen3-TTS","path":null,"label":"QwenLM/Qwen3-TTS","type":"external"},{"url":"https://github.com/QwenLM/Qwen-Image","path":null,"label":"QwenLM/Qwen-Image","type":"external"},{"url":"https://github.com/QwenLM/Qwen3-Omni","path":null,"label":"QwenLM/Qwen3-Omni","type":"external"},{"url":"https://github.com/QwenLM/qwen-code/releases/tag/v0.17.1","path":null,"label":"QwenLM/qwen-code","type":"external"},{"url":"https://github.com/QwenLM/qwen-code-examples/releases/tag/v0.1","path":null,"label":"QwenLM/qwen-code-examples","type":"external"},{"url":"https://github.com/QwenLM/qwen-code-action/releases/tag/v0.1.1","path":null,"label":"QwenLM/qwen-code-action","type":"external"},{"url":"https://qwenlm.github.io/blog/ofa/","path":null,"label":"qwenlm.github.io/blog","type":"external"},{"url":"https://qwenlm.github.io/blog/ofasys/","path":null,"label":"qwenlm.github.io/blog","type":"external"},{"url":"https://qwenlm.github.io/blog/chinese-clip/","path":null,"label":"qwenlm.github.io/blog","type":"external"},{"url":"https://qwenlm.github.io/blog/qwen/","path":null,"label":"qwenlm.github.io/blog","type":"external"},{"url":"https://qwenlm.github.io/blog/qwen1.5/","path":null,"label":"qwenlm.github.io/blog","type":"external"},{"url":"https://qwenlm.github.io/blog/qwen2/","path":null,"label":"qwenlm.github.io/blog","type":"external"},{"url":"https://qwenlm.github.io/blog/qwen2.5/","path":null,"label":"qwenlm.github.io/blog","type":"external"},{"url":"https://qwenlm.github.io/blog/qwen-moe/","path":null,"label":"qwenlm.github.io/blog","type":"external"},{"url":"https://qwenlm.github.io/blog/qwen-agent-2405/","path":null,"label":"qwenlm.github.io/blog","type":"external"},{"url":"https://qwenlm.github.io/blog/qwen2.5-turbo/","path":null,"label":"qwenlm.github.io/blog","type":"external"},{"url":"https://qwenlm.github.io/blog/qwen2-math/","path":null,"label":"qwenlm.github.io/blog","type":"external"},{"url":"https://qwenlm.github.io/blog/qwen2.5-math/","path":null,"label":"qwenlm.github.io/blog","type":"external"},{"url":"https://qwenlm.github.io/blog/qwen2.5-math-prm/","path":null,"label":"qwenlm.github.io/blog","type":"external"},{"url":"https://qwenlm.github.io/blog/qwq-32b-preview/","path":null,"label":"qwenlm.github.io/blog","type":"external"},{"url":"https://qwenlm.github.io/blog/qvq-72b-preview/","path":null,"label":"qwenlm.github.io/blog","type":"external"},{"url":"https://qwenlm.github.io/blog/codeqwen1.5/","path":null,"label":"qwenlm.github.io/blog","type":"external"},{"url":"https://qwenlm.github.io/blog/qwen2.5-coder/","path":null,"label":"qwenlm.github.io/blog","type":"external"},{"url":"https://qwenlm.github.io/blog/qwen2.5-coder-family/","path":null,"label":"qwenlm.github.io/blog","type":"external"},{"url":"https://qwenlm.github.io/blog/qwen-vl/","path":null,"label":"qwenlm.github.io/blog","type":"external"},{"url":"https://qwenlm.github.io/blog/qwen2-vl/","path":null,"label":"qwenlm.github.io/blog","type":"external"},{"url":"https://qwenlm.github.io/blog/qwen2-audio/","path":nul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