DeepSeek-V3.2
DeepSeek-V3.2 is an open-weights language model from DeepSeek, released December 1, 2025. It has 685B parameters (mixture-of-experts, 52B active). The context window is 160K tokens. On the Epoch Capabilities Index it scores 146.3, rank 90 of 256 rated models.
Check it against your own PC →
Can you run DeepSeek-V3.2 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 | Too large | – | – | – | – |
| 8 GB VRAM | Too large | – | – | – | – |
| 12 GB VRAM | Too large | – | – | – | – |
| 16 GB VRAM | Too large | – | – | – | – |
| 24 GB VRAM | Too large | – | – | – | – |
| 32 GB VRAM | Too large | – | – | – | – |
Strengths by category
ModelTape's 0–100 fit on Epoch AI benchmark results.
| Category | Score | Based on |
|---|---|---|
| Math | 43.4 | ProofBench, OTIS Mock AIME 2024-2025, FrontierMath-2025-02-28-Private, FrontierMath-Tier-4-2025-07-01-Private |
| Coding | 44.5 | Aider polyglot, Terminal Bench |
Benchmark results
| Benchmark (Epoch AI) | Score |
|---|---|
| OTIS Mock AIME | 87.8% |
| GPQA Diamond | 81.1% |
| Aider Polyglot | 74.2% |
| Terminal-Bench | 39.6% |
| FrontierMath-2025-02-28-Private | 38.8% |
| ProofBench | 8.0% |
| FrontierMath-Tier-4-2025-07-01-Private | 3.5% |
Links
Hugging Face: deepseek-ai/DeepSeek-V3.2-Exp-Base · Epoch AI benchmarks
Models with a similar score
DeepSeek-V4-Pro · GPT-5 · Grok 4.3 Beta · Qwen 3.6 Max (Preview) · GPT-5.4 Mini · Qwen 3.6 Plus · Kimi K2.5 · Inkling
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