← AI Hashrate 中文

Can RTX 5090 32GB run gemma-4-31B-it-FP8-block?

NVIDIA · 32 GB GDDR7 · 1792 GB/s bandwidth · RedHatAI · 31.3B · model ctx up to NoneK

✅ Yes — RTX 5090 32GB (32 GB) can run gemma-4-31B-it-FP8-block at Q4 (8K)
VRAM: 24.48 GB needed of 32 GB
Speed: ~62.1 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)
Q44K21.35 GBYes62.1 ± est.
Q48K default24.48 GBYes62.1 ± est.
Q432K43.26 GBNo56.9 ± est.
FP164K66.73 GBNo6.6 ± est.
FP168K default69.86 GBNo6.0 ± est.
FP1632K88.64 GBNo3.7 ± 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 neededRTX 5090 32GB VRAM
Q417.22 GB6.26 GB1 GB24.48 GB32 GB
FP1662.6 GB6.26 GB1 GB69.86 GB32 GB

Other GPUs that run gemma-4-31B-it-FP8-block

All GPUs for gemma-4-31B-it-FP8-block →

Other models for the RTX 5090 32GB

All models on the RTX 5090 32GB →