DeepSeek AI · deepseek2
Can I run deepseek-v2?
A strong, economical, and efficient Mixture-of-Experts language model.
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 contextdeepseek-v2 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 |
|---|---|---|---|
| deepseek-v2:16b16B parameters (tag)160K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q4_0 | 8.3 GB | ~10.4 GB |
| deepseek-v2:16b-lite-chat-q4_K_M16B parameters (tag)4K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q4_K_M | 9.7 GB | ~11.9 GB |
| deepseek-v2:16b-lite-chat-q5_K_M16B parameters (tag)4K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q5_K_M | 11.0 GB | ~13.4 GB |
| deepseek-v2:16b-lite-chat-q6_K16B parameters (tag)4K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q6_K | 13.1 GB | ~15.6 GB |
| deepseek-v2:16b-lite-chat-q8_016B parameters (tag)4K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q8_0 | 15.6 GB | ~18.2 GB |
| deepseek-v2:16b-lite-chat-fp1616B parameters (tag)4K documented maximum contextBuild sourceCatalog checked 2026-10-13 | F16 | 29.3 GB | ~33.1 GB |
| deepseek-v2:236b236B parameters (tag)4K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q4_0 | 123.8 GB | ~152.8 GB |
| deepseek-v2:236b-chat-q4_K_M236B parameters (tag)4K documented maximum contextBuild sourceCatalog checked 2026-10-13 | Q4_K_M | 132.7 GB | ~162.4 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 deepseek-v2 locally
- 1.Install Ollama for Windows, macOS or Linux.
- 2.Download this exact build in a terminal:
ollama pull deepseek-v2:16b - 3.Check the source for the build's task. For text generation, run
ollama run deepseek-v2:16b. Base/text builds may need a prompt template; an instruct build is usually the appropriate starting point for a conversation.
Frequently asked questions about deepseek-v2
- How much VRAM do I need to run deepseek-v2?
- At 4K context, the smallest published build of deepseek-v2 (Q4_0) needs roughly 10.4 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 deepseek-v2 without a dedicated GPU?
- A supported CPU runtime can use system RAM. The smallest listed build needs an estimated 10.4 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 deepseek-v2 download?
- The smallest published build is 8.3 GB. There are 12 builds in total, the largest being 439.2 GB. Leave some extra free disk space beyond the download itself.
- How do I run deepseek-v2 locally?
- Install Ollama, then download a specific build with "ollama pull deepseek-v2:16b". For a build that supports text generation, use ollama run with the same tag. Check the model source for its task and prompt format.
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Model data from the official Ollama registry · verified 13/10/2026