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Can V100 32GB SXM2 run qwen35b-a3b-fable-sft-abliterated?

NVIDIA · 32 GB HBM2 · 900 GB/s bandwidth · hotdogs · 34.7B (active 3.0B) · MoE · model ctx up to 32K

✅ Yes — V100 32GB SXM2 (32 GB) can run qwen35b-a3b-fable-sft-abliterated at Q4 (8K)
VRAM: 20.69 GB needed of 32 GB
Speed: ~322.4 tok/s (estimated)
BB · GoodComposite score: VRAM headroom × 0.5 + tok/s speed × 0.5. Q4 @ 8K context.
CUDA
Estimates from memory-bandwidth formula; rows marked "measured" override. Methodology.

Fit & speed by quant and context

QuantContextVRAM neededFits?tok/s (decode)
Q44K20.39 GBYes322.4 ± est.
Q48K default20.69 GBYes322.4 ± est.
Q432K22.49 GBYes322.4 ± est.
FP164K70.7 GBNo30.7 ± est.
FP168K default71.0 GBNo30.4 ± est.
FP1632K72.8 GBNo28.9 ± 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
Q419.09 GB0.6 GB1 GB20.69 GB32 GB
FP1669.4 GB0.6 GB1 GB71.0 GB32 GB

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