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Can V100 32GB SXM2 run DeepSeek-R1-0528-Qwen3-8B?

NVIDIA · 32 GB HBM2 · 900 GB/s bandwidth · DeepSeek · 8.2B · model ctx up to 128K

✅ Yes — V100 32GB SXM2 (32 GB) can run DeepSeek-R1-0528-Qwen3-8B at Q4 (8K)
VRAM: 6.72 GB needed of 32 GB
Speed: ~115.9 tok/s (estimated)
SS · ExcellentComposite score: VRAM headroom × 0.5 + tok/s speed × 0.5. Q4 @ 8K context.
CUDA
Excellent for 💬 chatExcellent for ⌨️ codingExcellent for 📋 general
Estimates from memory-bandwidth formula; rows marked "measured" override. Methodology.

Fit & speed by quant and context

QuantContextVRAM neededFits?tok/s (decode)
Q44K6.15 GBYes115.9 ± est.
Q48K default6.72 GBYes115.9 ± est.
Q432K10.09 GBYes115.9 ± est.
FP164K17.96 GBYes32.4 ± est.
FP168K default18.52 GBYes32.4 ± est.
FP1632K21.9 GBYes32.4 ± est.

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
Q44.59 GB1.12 GB1 GB6.72 GB32 GB
FP1616.4 GB1.12 GB1 GB18.52 GB32 GB

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