Openai Gpt Oss 20B speed on RTX 4060 and quantization-level VRAM fit.
RTX 4060 does not meet the minimum VRAM requirement for Q4 inference of Openai Gpt Oss 20B. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.
RTX 4060 lacks sufficient VRAM for comfortable Openai Gpt Oss 20B operation with Q4 quantization.
Your 8GB GPU is 3GB short of the 11GB minimum.
Options: (1) Try Q2 or Q3 quantization for lower VRAM requirements, (2) Consider cloud GPU rental, (3) Upgrade to a GPU with at least 16GB VRAM.
| Quantization | VRAM needed | VRAM available | Estimated speed | Verdict |
|---|---|---|---|---|
| Q4 | 11GB | 8GB | 24.68 tok/s | ❌ Not recommended |
| Q8 | 22GB | 8GB | 17.27 tok/s | ❌ Not recommended |
| FP16 | 44GB | 8GB | 9.38 tok/s | ❌ Not recommended |
Check current pricing links for RTX 4060 and similar cards.
Open RTX 4060 buy links →Use workload-focused recommendations before committing to a purchase.
Browse best GPU guides →Compare complete systems if you want ready-to-run hardware.
Compare prebuilt systems →Your GPU doesn't meet the VRAM requirements. Run Openai Gpt Oss 20B on cloud GPU instantly.
RTX 4060 is not a comfortable Q4 fit for Openai Gpt Oss 20B (about 11GB needed).
Q4 inference is estimated to need about 11GB VRAM on this page, while RTX 4060 has 8GB available.
Try lower-bit quantization, choose a smaller model, or move to a higher-VRAM GPU from the alternatives list.