← AI Hashrate 中文

Can V100 32GB SXM2 run NVIDIA-Nemotron-3-Super-120B-A12B-BF16?

NVIDIA · 32 GB HBM2 · 900 GB/s bandwidth · NVIDIA · 120.0B (active 12.0B) · MoE · model ctx up to 256K

❌ No — NVIDIA-Nemotron-3-Super-120B-A12B-BF16 Q4 needs 67.34 GB, card only has 32 GB
VRAM: 67.34 GB needed of 32 GB
Speed: ~30.4 tok/s (estimated)
FF · No FitComposite score: VRAM headroom × 0.5 + tok/s speed × 0.5. Q4 @ 8K context.
CUDA
Your GPU won't fit NVIDIA-Nemotron-3-Super-120B-A12B-BF16, but runs these similar models: Qwen3-8B, gemma-4-26B-A4B-itor☁️ 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)
Q44K67.34 GBNo30.7 ± est.
Q48K default67.69 GBNo30.4 ± est.
Q432K69.75 GBNo28.7 ± est.
FP164K241.34 GBNo
FP168K default241.69 GBNo
FP1632K243.75 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
Q466.0 GB0.69 GB1 GB67.69 GB32 GB
FP16240.0 GB0.69 GB1 GB241.69 GB32 GB

Other GPUs that run NVIDIA-Nemotron-3-Super-120B-A12B-BF16

All GPUs for NVIDIA-Nemotron-3-Super-120B-A12B-BF16 →

Other models for the V100 32GB SXM2

All models on the V100 32GB SXM2 →