DeepSeekMath-V2
DeepSeekMath-V2 is an open-weights language model from DeepSeek, released November 27, 2025. Its makers disclosed about 685B parameters.
Check it against your own PC →
Can you run DeepSeekMath-V2 locally?
Even with 32 GB of VRAM and 32 GB of RAM it is too large to run at a usable speed on a single consumer GPU. Estimates assume 32 GB of DDR5 RAM, a 16K context and llama.cpp-style GGUF quantization. Enter your exact hardware in the live app.
| GPU memory | Verdict | Best quant | VRAM | RAM | tok/s |
|---|---|---|---|---|---|
| 6 GB VRAM | Size unknown | – | – | – | – |
| 8 GB VRAM | Size unknown | – | – | – | – |
| 12 GB VRAM | Size unknown | – | – | – | – |
| 16 GB VRAM | Size unknown | – | – | – | – |
| 24 GB VRAM | Size unknown | – | – | – | – |
| 32 GB VRAM | Size unknown | – | – | – | – |
Parameter count unknown. The weights may not be on Hugging Face yet.
Benchmark results
Epoch AI has not published results for DeepSeekMath-V2 yet. New models are usually evaluated within days to weeks.
Links
Announcement · Hugging Face: xdrk14/DeepSeek-Math-V2
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