Can the NVIDIA RTX 2080 Ti 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 2080 Ti at Q2_K, which costs noticeable quality. Expect about 274 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 13.5 GB, more than the 11 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 2080 Ti
Run it in the cloud
Want full quality? Run gpt-oss 20B on a bigger rented GPU.
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Memory needed by quantization
At 8,192 tokens of context. The black line marks the 11 GB the NVIDIA RTX 2080 Ti can use.
| Quant | Quality | Memory | Fits? | Speed | |
|---|---|---|---|---|---|
| FP16 | Full quality | 42.6 GB | Too big | — | |
| Q8_0 | Near-lossless | 23 GB | Too big | — | |
| Q6_K | Excellent | 17.9 GB | Too big | — | |
| Q5_K_M | Very good | 15.7 GB | Too big | — | |
| Q4_K_M | Good, most popular | 13.5 GB | Too big | — | |
| Q3_K_M | Noticeably degraded | 11 GB | Too big | — | |
| Q2_K | Heavily degraded | 8.6 GB | Fits | ~274 tok/s |
Measured speed from real RTX 2080 Ti owners
Tokens per second that people measured on their own NVIDIA RTX 2080 Ti, next to our estimate.
No one has measured gpt-oss 20B on the NVIDIA RTX 2080 Ti yet. The speeds above are estimates. Run the benchmark and yours becomes the first real number on this page.
Have an RTX 2080 Ti? Add your real speed
One command times gpt-oss 20B in your own Ollama, shows you exactly what it would send, and asks before sending anything. No sign-up, no personal data.
macOS and Linux
curl -fsSL https://gpufit.dev/bench.sh | sh -s -- gpt-oss:20bWindows (PowerShell)
$env:GPUFIT_MODEL="gpt-oss:20b"; irm https://gpufit.dev/bench.ps1 | iexGPUs that run gpt-oss 20B comfortably
Models that run well on the NVIDIA RTX 2080 Ti
Frequently asked questions
Can NVIDIA RTX 2080 Ti run gpt-oss 20B?
Only just. gpt-oss 20B fits on the NVIDIA RTX 2080 Ti at Q2_K, which costs noticeable quality. Expect about 274 tokens/second. A card with more memory is a better experience.
How much VRAM does gpt-oss 20B need?
About 13.5 GB at Q4_K_M with 8,192 tokens of context, and about 42.6 GB at full FP16 precision.
How fast is gpt-oss 20B on the NVIDIA RTX 2080 Ti?
Roughly 274 tokens per second at Q2_K, estimated from the NVIDIA RTX 2080 Ti's 616 GB/s memory bandwidth.