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gemma-3-4b-it

Gemma 3 4B Instruct is Google's compact instruction-following model, targeting deployment on single-GPU and edge devices. It covers both text and image inputs and is suitable for conversational AI applications with moderate resource constraints.

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From the model card

Fields below are copied from the tags and counters on the HuggingFace repository google/gemma-3-4b-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
image-text-to-text
Library
Transformers
Weight formats
safetensors
License tag
gemma — read the license file in the repo before relying on it
Lineage
Papers cited
arXiv:1905.07830, arXiv:1905.10044, arXiv:1911.11641, arXiv:1904.09728, arXiv:1705.03551, arXiv:1911.01547, arXiv:1907.10641, arXiv:1903.00161, arXiv:2009.03300, arXiv:2304.06364, arXiv:2103.03874, arXiv:2110.14168, arXiv:2311.12022, arXiv:2108.07732, arXiv:2107.03374, arXiv:2210.03057, arXiv:2106.03193, arXiv:1910.11856, arXiv:2502.12404, arXiv:2502.21228, arXiv:2404.16816, arXiv:2104.12756, arXiv:2311.16502, arXiv:2203.10244, arXiv:2404.12390, arXiv:1810.12440, arXiv:1908.02660, arXiv:2312.11805
Downloads (HF counter at last fetch)
1,542,803
Likes (HF counter at last fetch)
1,470
Model card
https://huggingface.co/google/gemma-3-4b-it

Use cases

  • Lightweight instruction-following assistant on consumer hardware
  • Multimodal chat with image understanding at 4B scale
  • Fine-tuning base for constrained deployment scenarios
  • Embedded AI features in apps where a 7B+ model is too large

Pros

  • 4B scale runs comfortably on 8GB VRAM
  • Supports image input via Gemma 3's multimodal architecture
  • Gemma license permits commercial use with attribution
  • Google-maintained with documented benchmark results

Cons

  • Gemma license has more restrictions than Apache-2.0
  • Instruction following quality notably weaker than Llama 3.2 3B on many benchmarks
  • Vision capability is limited compared to dedicated VLMs
  • Model card has limited information on specific training data composition

Tags

transformerssafetensorsgemma3image-text-to-textconversationalarxiv:1905.07830arxiv:1905.10044arxiv:1911.11641arxiv:1904.09728arxiv:1705.03551arxiv:1911.01547arxiv:1907.10641arxiv:1903.00161arxiv:2009.03300arxiv:2304.06364arxiv:2103.03874arxiv:2110.14168arxiv:2311.12022arxiv:2108.07732arxiv:2107.03374