Can the NVIDIA RTX 4070 Ti Super run gpt-oss 20B?
- FP16
- Q8_0
- Q6_K
- Q5_K_M
- Q4_K_M
- Q3_K_M
- Q2_K
Yes. The NVIDIA RTX 4070 Ti Super can run gpt-oss 20B fully in VRAM at Q5_K_M (very good), using about 15.9 GB of the 16 GB available, at roughly 157 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 13.7 GB here). You have room for Q5_K_M, which is very good: pick that GGUF in LM Studio or from Hugging Face.
Run it in the cloud
No NVIDIA RTX 4070 Ti Super? 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 16 GB the NVIDIA RTX 4070 Ti Super 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 | Fits | ~157 tok/s | |
| Q4_K_M | Good, most popular | 13.7 GB | Fits | ~185 tok/s | |
| Q3_K_M | Noticeably degraded | 11.2 GB | Fits | ~229 tok/s | |
| Q2_K | Heavily degraded | 8.8 GB | Fits | ~299 tok/s |
GPUs that run gpt-oss 20B comfortably
Models that run well on the NVIDIA RTX 4070 Ti Super
Frequently asked questions
Can NVIDIA RTX 4070 Ti Super run gpt-oss 20B?
Yes. The NVIDIA RTX 4070 Ti Super can run gpt-oss 20B fully in VRAM at Q5_K_M (very good), using about 15.9 GB of the 16 GB available, at roughly 157 tokens/second.
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 4070 Ti Super?
Roughly 157 tokens per second at Q5_K_M, estimated from the NVIDIA RTX 4070 Ti Super's 672 GB/s memory bandwidth.