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gemma-2-9b-it

Gemma 2 9B Instruct is Google's instruction-tuned 9B model from the Gemma 2 family, which introduced sliding window + full attention alternation and logit soft-capping for improved training stability. At release it outperformed Llama 3 8B on multiple benchmarks while remaining smaller, making it one of the most downloaded open instruction models in its size class. It is English-focused with some multilingual capability.

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Fields below are copied from the tags and counters on the HuggingFace repository google/gemma-2-9b-it at our last fetch. They are set by the uploader, not verified by us; rows with no tag are omitted. How this page is made.

Publisher (HF namespace)
google
Pipeline tag
text-generation
Library
Transformers
Weight formats
safetensors
License tag
gemma — read the license file in the repo before relying on it
Lineage
Papers cited
arXiv:2009.03300, arXiv:1905.07830, arXiv:1911.11641, arXiv:1904.09728, arXiv:1905.10044, arXiv:1907.10641, arXiv:1811.00937, arXiv:1809.02789, arXiv:1911.01547, arXiv:1705.03551, arXiv:2107.03374, arXiv:2108.07732, arXiv:2110.14168, arXiv:2009.11462, arXiv:2101.11718, arXiv:2110.08193, arXiv:1804.09301, arXiv:2109.07958, arXiv:1804.06876, arXiv:2103.03874, arXiv:2304.06364, arXiv:2206.04615, arXiv:2203.09509
Downloads (HF counter at last fetch)
668,352
Likes (HF counter at last fetch)
920
Model card
https://huggingface.co/google/gemma-2-9b-it

Use cases

  • General-purpose chat assistant deployment on mid-range GPU hardware
  • Instruction following for content generation and summarisation
  • Code explanation and light code generation tasks
  • RAG-grounded QA with a capable sub-10B model
  • Fine-tuning baseline for specific instruction following domains

Pros

  • Competitive benchmark performance against Llama 3 8B at similar parameter count
  • Apache 2.0 license; Azure and TGI deployment supported
  • 804 likes; one of the most widely validated open 9B models
  • Sliding window + full attention hybrid improves long-context coherence

Cons

  • 9B scale is outpaced by Qwen3-8B and Llama 3.1-8B on many 2025 benchmarks
  • Gemma 2 is not the latest Gemma generation; Gemma 3 supersedes it
  • Logit soft-capping can occasionally produce oddly confident outputs
  • Lacks native multimodal capability present in Gemma 3

Tags

transformerssafetensorsgemma2text-generationconversationalarxiv:2009.03300arxiv:1905.07830arxiv:1911.11641arxiv:1904.09728arxiv:1905.10044arxiv:1907.10641arxiv:1811.00937arxiv:1809.02789arxiv:1911.01547arxiv:1705.03551arxiv:2107.03374arxiv:2108.07732arxiv:2110.14168arxiv:2009.11462arxiv:2101.11718