Can the NVIDIA RTX 5090 run gpt-oss 20B?
- FP16
- Q8_0
- Q6_K
- Q5_K_M
- Q4_K_M
- Q3_K_M
- Q2_K
Yes. The NVIDIA RTX 5090 can run gpt-oss 20B fully in VRAM at Q8_0 (near-lossless), using about 23 GB of the 32 GB available, at roughly 281 tokens/second.
Run it with Ollama
With Ollama installed, one command downloads and starts gpt-oss 20B:
ollama run gpt-oss:20bOllama's default download is Q4_K_M (about 13.5 GB here). You have room for Q8_0, which is near-lossless: pick that GGUF in LM Studio or from Hugging Face.
New to this? Step-by-step setup for the RTX 5090
Run it in the cloud
No NVIDIA RTX 5090? Run gpt-oss 20B in the cloud.
Rent a cloud GPU by the hour. No upfront cost, stop any time.
Memory needed by quantization
At 8,192 tokens of context. The black line marks the 32 GB the NVIDIA RTX 5090 can use.
| Quant | Quality | Memory | Fits? | Speed | |
|---|---|---|---|---|---|
| FP16 | Full quality | 42.6 GB | Too big | — | |
| Q8_0 | Near-lossless | 23 GB | Fits | ~281 tok/s | |
| Q6_K | Excellent | 17.9 GB | Fits | ~364 tok/s | |
| Q5_K_M | Very good | 15.7 GB | Fits | ~420 tok/s | |
| Q4_K_M | Good, most popular | 13.5 GB | Fits | ~493 tok/s | |
| Q3_K_M | Noticeably degraded | 11 GB | Fits | ~611 tok/s | |
| Q2_K | Heavily degraded | 8.6 GB | Fits | ~796 tok/s |
Measured speed from real RTX 5090 owners
Tokens per second that people measured on their own NVIDIA RTX 5090, next to our estimate.
No one has measured gpt-oss 20B on the NVIDIA RTX 5090 yet. The speeds above are estimates. Run the benchmark and yours becomes the first real number on this page.
Have an RTX 5090? 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
Frequently asked questions
Can NVIDIA RTX 5090 run gpt-oss 20B?
Yes. The NVIDIA RTX 5090 can run gpt-oss 20B fully in VRAM at Q8_0 (near-lossless), using about 23 GB of the 32 GB available, at roughly 281 tokens/second.
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 5090?
Roughly 281 tokens per second at Q8_0, estimated from the NVIDIA RTX 5090's 1792 GB/s memory bandwidth.