Can the GeForce RTX 5070 run gpt-oss-20b?
Only with CPU offload 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 12GB, about 1.2 GiB more than the card has.
All three quants
12GB card| Quant | Weights | With reserve | Verdict | Headroom |
|---|---|---|---|---|
| Q4_K_Mthe everyday quant | 11.7 GiB | 13.2 GiB | Only with CPU offload | short 1.2 GiB |
| Q8_0near-lossless | 20.7 GiB | 22.2 GiB | Only with CPU offload | short 10.2 GiB |
| FP16full weights | 39.1 GiB | 40.6 GiB | Does not fit | short 28.6 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.
Not this card. These fit it comfortably at Q4.
- GeForce RTX 5090 32GB · headroom 18.8 GiB
- GeForce RTX 3090 (used) 24GB · headroom 10.8 GiB
- GeForce RTX 4090 (used) 24GB · headroom 10.8 GiB
- Radeon RX 7900 XTX 24GB · headroom 10.8 GiB
What the GeForce RTX 5070 does run well → · gpt-oss-20b on every card →
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 →