01.AI · llama
Can I run yi-coder?
Yi-Coder is a series of open-source code language models that delivers state-of-the-art coding performance with fewer than 10 billion parameters.
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 contextyi-coder 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 |
|---|---|---|---|
| yi-coder:1.5b-base-q4_01.5B parameters (tag)128K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q4_0 | 0.8 GB | ~2.1 GB |
| yi-coder:1.5b1.5B parameters (tag)128K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q4_0 | 0.8 GB | ~2.1 GB |
| yi-coder:1.5b-base-q4_K_M1.5B parameters (tag)128K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q4_K_M | 0.9 GB | ~2.2 GB |
| yi-coder:1.5b-chat-q4_K_M1.5B parameters (tag)128K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q4_K_M | 0.9 GB | ~2.2 GB |
| yi-coder:1.5b-base-q5_K_M1.5B parameters (tag)128K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q5_K_M | 1.0 GB | ~2.3 GB |
| yi-coder:1.5b-chat-q5_K_M1.5B parameters (tag)128K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q5_K_M | 1.0 GB | ~2.3 GB |
| yi-coder:1.5b-base-q6_K1.5B parameters (tag)128K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q6_K | 1.2 GB | ~2.5 GB |
| yi-coder:1.5b-chat-q6_K1.5B parameters (tag)128K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q6_K | 1.2 GB | ~2.5 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 yi-coder locally
- 1.Install Ollama for Windows, macOS or Linux.
- 2.Download this exact build in a terminal:
ollama pull yi-coder:1.5b-base-q4_0 - 3.Check the source for the build's task. For text generation, run
ollama run yi-coder:1.5b-base-q4_0. Base/text builds may need a prompt template; an instruct build is usually the appropriate starting point for a conversation.
Frequently asked questions about yi-coder
- How much VRAM do I need to run yi-coder?
- At 4K context, the smallest published build of yi-coder (Q4_0) needs roughly 2.1 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 yi-coder without a dedicated GPU?
- A supported CPU runtime can use system RAM. The smallest listed build needs an estimated 2.1 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 yi-coder download?
- The smallest published build is 0.8 GB. There are 24 builds in total, the largest being 16.4 GB. Leave some extra free disk space beyond the download itself.
- How do I run yi-coder locally?
- Install Ollama, then download a specific build with "ollama pull yi-coder:1.5b-base-q4_0". 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 yi-coder 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