Can I Run / GPT-OSS 20B / on AMD RX 7900 XT

Can I Run GPT-OSS 20B on a AMD RX 7900 XT?

Yes

Runs comfortably at Q6_K — minimal quality loss.

Model size
21.5B
GPU memory
20.0GB
Smallest quant
Q2_K
Best fit
Q6_K

10 quantizations fit your 20.0GB

QuantMin VRAMRecommendedFile sizeHeadroom
Q6_KBEST18.7 GB20.2 GB12.0 GB+1.3 GB
Q5_K_M16.3 GB17.8 GB11.7 GB+3.7 GB
Q5_K_S15.8 GB17.3 GB11.7 GB+4.2 GB
Q4_114.4 GB15.9 GB11.6 GB+5.6 GB
Q4_K_M14.0 GB15.5 GB11.6 GB+6.0 GB
Q4_K_S13.3 GB14.8 GB11.6 GB+6.7 GB
Q4_013.1 GB14.6 GB11.5 GB+6.9 GB
Q3_K_M10.0 GB11.5 GB11.5 GB+10.0 GB
Q3_K_S9.3 GB10.8 GB11.5 GB+10.7 GB
Q2_K8.1 GB9.6 GB11.5 GB+11.9 GB

Try it in the cloud first

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Full model details
GPT-OSS 20B

All quant variants, benchmark scores, and use-case tags.

Best models for this GPU
AMD RX 7900 XT

Top-ranked open-source models that fit in 20.0GB.

FAQ

Can the AMD RX 7900 XT run GPT-OSS 20B?

Yes. The AMD RX 7900 XT's 20.0GB of VRAM is enough to run GPT-OSS 20B at Q6_K quantization (18.7GB required).

What's the best quantization to use?

Q6_K is the highest-precision quantization that fits in your 20.0GB. It uses about 18.7GB of memory and 20.2GB recommended for comfortable inference.

What if I need more headroom for context length?

KV cache memory grows with context length. The numbers above assume a baseline 2K-4K context. For long-context use (32K+), add another 2-6GB depending on the model architecture.