Can the GeForce RTX 5070 run gpt-oss-120b?
Does not fit at Q4_K_M.
gpt-oss-120b is 117B parameters (MoE; all experts resident). At Q4_K_M the weights are about 65.4 GiB; with the 1.5 GiB runtime reserve that is 66.9 GiB against the card's 12GB, about 54.9 GiB more than the card has.
All three quants
12GB card| Quant | Weights | With reserve | Verdict | Headroom |
|---|---|---|---|---|
| Q4_K_Mthe everyday quant | 65.4 GiB | 66.9 GiB | Does not fit | short 54.9 GiB |
| Q8_0near-lossless | 115.5 GiB | 117.0 GiB | Does not fit | short 105.0 GiB |
| FP16full weights | 217.9 GiB | 219.4 GiB | Does not fit | short 207.4 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.
Nothing in the consumer catalog fits gpt-oss-120b at Q4 on a single card; this is multi-GPU or datacenter territory, or a job for hosted inference (see PicksByModel for per-token pricing).
What the GeForce RTX 5070 does run well → · gpt-oss-120b on every card →
About the model
gpt-oss-120b by OpenAI: 131,072-token native context, text, released 2025 under the Apache-2.0. Model card → · Hosted pricing on PicksByModel →