Can the NVIDIA RTX 3080 10GB run gpt-oss 20B?
- FP16
- Q8_0
- Q6_K
- Q5_K_M
- Q4_K_M
- Q3_K_M
- Q2_K
Only just. gpt-oss 20B fits on the NVIDIA RTX 3080 10GB at Q2_K, which costs noticeable quality. Expect about 338 tokens/second. A card with more memory is a better experience.
Run it with Ollama
Ollama's default gpt-oss:20b download is Q4_K_M, which needs about 13.7 GB, more than the 10 GB available. Download the Q2_K GGUF instead (LM Studio lists quants per model), or try a smaller context length.
New to this? Step-by-step setup for the RTX 3080 10GB
Run it in the cloud
Want full quality? Run gpt-oss 20B on a bigger rented GPU.
Rent a cloud GPU by the hour. No upfront cost, stop any time. Not sure whether to rent or buy? Compare the cost.
Memory needed by quantization
At 8,192 tokens of context. The black line marks the 10 GB the NVIDIA RTX 3080 10GB can use.
| Quant | Quality | Memory | Fits? | Speed | |
|---|---|---|---|---|---|
| FP16 | Full quality | 42.8 GB | Too big | — | |
| Q8_0 | Near-lossless | 23.2 GB | Too big | — | |
| Q6_K | Excellent | 18.1 GB | Too big | — | |
| Q5_K_M | Very good | 15.9 GB | Too big | — | |
| Q4_K_M | Good, most popular | 13.7 GB | Too big | — | |
| Q3_K_M | Noticeably degraded | 11.2 GB | Too big | — | |
| Q2_K | Heavily degraded | 8.8 GB | Fits | ~338 tok/s |
GPUs that run gpt-oss 20B comfortably
Models that run well on the NVIDIA RTX 3080 10GB
Frequently asked questions
Can NVIDIA RTX 3080 10GB run gpt-oss 20B?
Only just. gpt-oss 20B fits on the NVIDIA RTX 3080 10GB at Q2_K, which costs noticeable quality. Expect about 338 tokens/second. A card with more memory is a better experience.
How much VRAM does gpt-oss 20B need?
About 13.7 GB at Q4_K_M with 8,192 tokens of context, and about 42.8 GB at full FP16 precision.
How fast is gpt-oss 20B on the NVIDIA RTX 3080 10GB?
Roughly 338 tokens per second at Q2_K, estimated from the NVIDIA RTX 3080 10GB's 760 GB/s memory bandwidth.