← AI Hashrate

Can RTX 3090 Ti 24GB run gpt-oss-20b?

NVIDIA · 24 GB GDDR6X · 1008 GB/s bandwidth · OpenAI · 21.5B (active 3.6B) · MoE · model ctx up to 128K

Yes — the RTX 3090 Ti 24GB (24 GB GDDR6X) can run gpt-oss-20b. At Q4 with the default 8K context it needs ≈ 13.55 GB VRAM (weights 11.83 GB + KV cache 0.72 GB + 1 GB runtime overhead), which fits within 24 GB. Decode at Q4/8K: ≈ 178.2 tok/s (estimated, batch 1). FP16 needs ≈ 44.72 GB — does not fit on this card. Estimates come from memory-bandwidth math; rows tagged measured override estimates. Relative ranking is more reliable than absolute tok/s. Methodology.

Fit & speed by quant and context

QuantContextVRAM neededFits?tok/s (decode)
Q44K13.19 GBYes178.2 est.
Q48K default13.55 GBYes178.2 est.
Q432K15.71 GBYes178.2 est.
FP164K44.36 GBNo41.0 est.
FP168K default44.72 GBNo40.3 est.
FP1632K46.88 GBNo36.7 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 3090 Ti 24GB VRAM
Q411.83 GB0.72 GB1 GB13.55 GB24 GB
FP1643.0 GB0.72 GB1 GB44.72 GB24 GB

Other GPUs that run gpt-oss-20b

All GPUs for gpt-oss-20b →

Other models for the RTX 3090 Ti 24GB

All models on the RTX 3090 Ti 24GB →