{"schema_version":"onlylabs.public_signal.v1","title":"Google (DeepMind / Gemini) Model: google/gemma-4-26B-A4B-it-assistant","description":"Google (DeepMind / Gemini) model signal with public source context, captured evidence pages, related signals, and data-business radar classification.","url":"https://onlylabs.fyi/signals/9e927ea2-d026-4b03-b840-197418c6a577","json_url":"https://onlylabs.fyi/signals/9e927ea2-d026-4b03-b840-197418c6a577/signal.json","generated_at":"2026-06-11T02:40:55.600002+00:00","org":{"slug":"google-deepmind","name":"Google (DeepMind / Gemini)","category":"frontier-lab","category_label":"Frontier lab","dossier_url":"https://onlylabs.fyi/labs/google-deepmind","dossier_json_url":"https://onlylabs.fyi/labs/google-deepmind/dossier.json"},"related_urls":{"signal":"https://onlylabs.fyi/signals/9e927ea2-d026-4b03-b840-197418c6a577","signal_json":"https://onlylabs.fyi/signals/9e927ea2-d026-4b03-b840-197418c6a577/signal.json","source":"https://huggingface.co/google/gemma-4-26B-A4B-it-assistant","lab_dossier":"https://onlylabs.fyi/labs/google-deepmind","lab_dossier_json":"https://onlylabs.fyi/labs/google-deepmind/dossier.json","analysis":"https://onlylabs.fyi/analysis/google-deepmind","analysis_json":"https://onlylabs.fyi/analysis/google-deepmind/analysis.json","analysis_evidence_json":"https://onlylabs.fyi/analysis/google-deepmind/evidence.json","category":"https://onlylabs.fyi/frontier","category_json":"https://onlylabs.fyi/frontier.json","category_feed":"https://onlylabs.fyi/frontier/feed.xml","category_signals_json":"https://onlylabs.fyi/signals.json","topic":"https://onlylabs.fyi/topics/releases","topic_signals_json":"https://onlylabs.fyi/topics/releases/signals.json","topic_feed":"https://onlylabs.fyi/topics/releases/feed.xml","data_business":null},"answer_pack":{"answer":"Google (DeepMind / Gemini) published google/gemma-4-26B-A4B-it-assistant. 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MTP is implemented by extending the base model with a smaller, faster draft model. When used in a Speculative Decoding pipeline, the draft model predicts several tokens ahead, which the target model then verifies in parallel. This results in significant decoding speedups (up to 3x) while guaranteeing the exact same quality as standard generation, making these..."},"evidence_pages":[{"url":"https://huggingface.co/google/gemma-4-26B-A4B-it-assistant/raw/main/README.md","final_url":"https://huggingface.co/google/gemma-4-26B-A4B-it-assistant/raw/main/README.md","title":"google/gemma-4-26B-A4B-it-assistant model card","http_status":200,"content_type":"text/plain; charset=utf-8","capture_method":"plain","fetched_at":"2026-06-11T02:40:55.600002+00:00","bytes":28685,"raw_path":"927089a7b6a7255a5c2f0e6b4b6a0eb60f3de06ac2ea5312f29eba3a8371c9b5.md","content_hash":"0193e4a2ad88a1d9835cae24b306d207827a88fa985acb0d03d5fa572e59ff8b","excerpt_chars":1200,"truncated":true,"excerpt":"--- library_name: transformers license: apache-2.0 license_link: https://ai.google.dev/gemma/docs/gemma_4_license pipeline_tag: any-to-any --- <div align=\"center\"> <img src=https://ai.google.dev/gemma/images/gemma4_banner.png> </div> <p align=\"center\"> <a href=\"https://huggingface.co/collections/google/gemma-4\" target=\"_blank\">Hugging Face</a> | <a href=\"https://github.com/google-gemma\" target=\"_blank\">GitHub</a> | <a href=\"https://ai.google.dev/gemma/docs/mtp/mtp\" target=\"_blank\">MTP Documentation</a> <br> <b>License</b>: <a href=\"https://ai.google.dev/gemma/docs/gemma_4_license\" target=\"_blank\">Apache 2.0</a> | <b>Authors</b>: <a href=\"https://deepmind.google/models/gemma/\" target=\"_blank\">Google DeepMind</a> </p> > [!Note] > This model card is for the Multi-Token Prediction (MTP) drafters for the Gemma 4 models. 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