👁 DeepSeek
DeepSeek
DeepSeek V3.2
Frontier
Jan 2026Released128K tokensContextMITLicense90 ExceptionalQuality
DeepSeek V3.2 (671B parameters) requires approximately 411.6 GB of VRAM with Q4_K_M quantization. As a Mixture of Experts model with 37B active parameters, it uses less memory than its total parameter count suggests. For the best balance of quality and speed, we recommend hardware with at least 474 GB of VRAM.
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— copy & paste to run locallyCopy-paste commands to run DeepSeek V3.2 on your machine.
Run
ollama run deepseek-v3.2Quick specs
Parameters671B (37B active)
Architecturemoe (MoE)
Context128K tokens
Modalitytext
Min RAM261.7 GB
Rec. RAM409.3 GB (Q4_K_M)
LicenseMIT
FamilyDeepSeek
✓ Code✓ Chat✓ Reasoning
About this model
- •671B total / 37B active MoE
- •DeepSeek Sparse Attention
- •128K context
- •MIT license
- •67.8% SWE-bench Verified
Related models
Your hardware
Detecting...
Quantization options
VRAM estimates by quant level
No hardware detected — fit column shows raw VRAM estimates
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 261.7 GB | Low | — |
Q3_K_S | 3 | 328.8 GB | Low | — |
NVFP4 | 4 | 375.8 GB | Medium | — |
Q4_K_M | 4 | 409.3 GB | Medium | — |
Q5_K_M | 5 | 483.1 GB | High | — |
Q6_K | 6 | 550.2 GB | High | — |
Q8_0 | 8 | 718.0 GB | Very High | — |
F16 | 16 | 1375.6 GB | Maximum | — |
Quality benchmarks
DeepSeek V3.2 benchmark scores
Coding
SWE-bench Verified—
HumanEval+—
Aider Polyglot—
LiveCodeBench74.1%
Reasoning
MMLU-Pro85.0%
GPQA Diamond—
MATH-500—
ARC Challenge—
Source: official · 2025-12-01
Hardware compatibility
Fit estimates across all hardware
Computing compatibility...
Memory breakdown
Reference: RTX 2060 6GB
Weights409.3 GB
KV Cache0.5 GB
Runtime1.2 GB
Headroom0.6 GB
Frequently asked questions
FAQ — DeepSeek V3.2
See also