← AI Hashrate 中文

Can V100 32GB SXM2 run DeepSeek-R1?

NVIDIA · 32 GB HBM2 · 900 GB/s bandwidth · DeepSeek · 684.5B (active 37B) · MoE · model ctx up to 128K

❌ No — DeepSeek-R1 Q4 needs 384.15 GB, card only has 32 GB
VRAM: 384.15 GB needed of 32 GB
FF · No FitComposite score: VRAM headroom × 0.5 + tok/s speed × 0.5. Q4 @ 8K context.
CUDA
Your GPU won't fit DeepSeek-R1, but runs these similar models: Qwen3.6-27B, DeepSeek-R1-0528-Qwen3-8Bor☁️ Rent on RunPod from ~$0.50/hr
Estimates from memory-bandwidth formula; rows marked "measured" override. Methodology.

Fit & speed by quant and context

QuantContextVRAM neededFits?tok/s (decode)
Q44K384.15 GBNo
Q48K default390.82 GBNo
Q432K430.85 GBNo
FP164K1376.67 GBNo
FP168K default1383.34 GBNo
FP1632K1423.38 GBNo

Fits = weights + KV(ctx) + 1 GB overhead ≤ 95% of VRAM. Measured anchors are context-agnostic; the fit verdict is recomputed per context. A missing tok/s means the model is far beyond this card (offload-only territory).

VRAM breakdown at 8K context

QuantWeightsKV cacheOverheadTotal neededV100 32GB SXM2 VRAM
Q4376.48 GB13.34 GB1 GB390.82 GB32 GB
FP161369.0 GB13.34 GB1 GB1383.34 GB32 GB

Other GPUs that run DeepSeek-R1

All GPUs for DeepSeek-R1 →

Other models for the V100 32GB SXM2

All models on the V100 32GB SXM2 →