Can the GeForce RTX 4090 (used) run gpt-oss-20b?
Fits comfortably at Q4_K_M.
gpt-oss-20b is 21B parameters (MoE; all experts resident). At Q4_K_M the weights are about 11.7 GiB; with the 1.5 GiB runtime reserve that is 13.2 GiB against the card's 24GB, leaving about 10.8 GiB for context.
All three quants
24GB card| Quant | Weights | With reserve | Verdict | Headroom |
|---|---|---|---|---|
| Q4_K_Mthe everyday quant | 11.7 GiB | 13.2 GiB | Fits comfortably | 10.8 GiB |
| Q8_0near-lossless | 20.7 GiB | 22.2 GiB | Fits, tight on context | 1.8 GiB |
| FP16full weights | 39.1 GiB | 40.6 GiB | Only with CPU offload | short 16.6 GiB |
Verdict rules: fits comfortably when weights plus reserve sit within 85% of VRAM; tight when they fit with little left for context; CPU offload when they exceed VRAM by up to 2x (runs, slowly, with layers in system RAM); no beyond that. The KV cache per token depends on the model's architecture and is not modelled here.
Good match. Get the card.
The GeForce RTX 4090 (used) clears gpt-oss-20b at Q4_K_M and at Q8_0. Live listings below; this page was rebuilt 2026-08-23.
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About the model
gpt-oss-20b by OpenAI: 131,072-token native context, text, released 2025 under the Apache-2.0. Model card → · Hosted pricing on PicksByModel →