Google DeepMind · gemma3
Can I run gemma3?
The current, most capable model that runs on a single GPU.
Parameter counts and memory belong to each build below. A family can contain several sizes and tasks; fitting in memory is not a quality ranking.
Calculate memory for a build and contextgemma3 system requirements
Memory needed at 4K context, counting model weights, KV cache, compute buffers and runtime overhead. Download sizes come from the official Ollama registry.
| Build | Quantization | Download | Memory needed |
|---|---|---|---|
| gemma3:270m270M parameters (tag)32K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q8_0 | 0.3 GB | ~0.9 GB |
| gemma3:270m-it-fp16270M parameters (tag)32K documented maximum contextBuild sourceCatalog checked 2026-10-13 | F16 | 0.5 GB | ~1.1 GB |
| gemma3:1b1B parameters (tag)32K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q4_K_M | 0.8 GB | ~1.4 GB |
| gemma3:1b-it-q8_01B parameters (tag)32K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q8_0 | 1.0 GB | ~1.6 GB |
| gemma3:1b-it-fp161B parameters (tag)32K documented maximum contextBuild sourceCatalog checked 2026-10-13 | F16 | 1.9 GB | ~2.5 GB |
| gemma3:4b4B parameters (tag)128K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q4_K_M | 3.1 GB | ~3.4 GB |
| gemma3:4b-it-q8_04B parameters (tag)128K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q8_0 | 4.6 GB | ~5.1 GB |
| gemma3:12b12B parameters (tag)128K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q4_K_M | 7.6 GB | ~9.2 GB |
Showing the 8 smallest non-alias builds. Choose any build and change the context. A context above the build's documented maximum is a hypothetical calculation, not a supported setting.
How to run gemma3 locally
- 1.Install Ollama for Windows, macOS or Linux.
- 2.Download this exact build in a terminal:
ollama pull gemma3:270m - 3.Check the source for the build's task. For text generation, run
ollama run gemma3:270m. Base/text builds may need a prompt template; an instruct build is usually the appropriate starting point for a conversation.
Frequently asked questions about gemma3
- How much VRAM do I need to run gemma3?
- At 4K context, the smallest published build of gemma3 (Q8_0) needs roughly 0.9 GB of GPU memory once weights, KV cache, compute buffers and runtime overhead are counted. Bigger quantizations and longer context windows need more. It can also run partly or entirely on the CPU using system RAM, more slowly.
- Can I run gemma3 without a dedicated GPU?
- A supported CPU runtime can use system RAM. The smallest listed build needs an estimated 0.9 GB at 4K context, plus headroom for your operating system. Check the build's runtime requirements. We have not measured its speed on your CPU.
- How big is the gemma3 download?
- The smallest published build is 0.3 GB. There are 14 builds in total, the largest being 51.1 GB. Leave some extra free disk space beyond the download itself.
- How do I run gemma3 locally?
- Install Ollama, then download a specific build with "ollama pull gemma3:270m". For a build that supports text generation, use ollama run with the same tag. Check the model source for its task and prompt format.
Will gemma3 run on your PC?
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Compare with similar models
Or start from your memory: 8 GB VRAM, 12 GB VRAM, 16 GB VRAM, 24 GB VRAM or a 16 GB Mac.
Model data from the official Ollama registry · verified 13/10/2026