How fast will GPT-OSS 20B feel on the A100 80GB (cloud)?

GPT-OSS 20B on the A100 80GB (cloud)

GPT-OSS 20B is a 20.91B-parameter mixture-of-experts model (3.6B active per token). At MXFP4 it needs about 12.9 GB of memory. The A100 80GB (cloud) has 74 GB usable, so it fits entirely in memory. Expect about 394 tokens/sec (143–645), with the first token after 0.3 s for a short prompt. This estimate is interpolated from benchmarks of similar setups.

Speed by quantization

Quantization	File size	Memory	Generation	First token	Source
MXFP4	12.1 GB	Fits	394 tok/s	0.3 s	Derived

GPT-OSS 20B on other hardware

H100 80GB (cloud) · 648 tok/s at MXFP4
NVIDIA RTX 5090 32GB · 347 tok/s at MXFP4
NVIDIA RTX PRO 6000 96GB · 347 tok/s at MXFP4
H200 141GB (cloud) · 306 tok/s at MXFP4
AMD RX 7900 XTX 24GB · 288 tok/s at MXFP4
Mac Studio M5 Ultra 512GB · 272 tok/s at MXFP4
Mac Studio M3 Ultra 512GB · 204 tok/s at MXFP4
NVIDIA RTX 4090 24GB · 195 tok/s at MXFP4
NVIDIA RTX 5080 16GB · 186 tok/s at MXFP4
NVIDIA RTX 3090 24GB · 181 tok/s at MXFP4
NVIDIA RTX 5070 Ti 16GB · 173 tok/s at MXFP4
AMD Radeon AI PRO R9700 32GB · 159 tok/s at MXFP4
MacBook Pro M5 Max 128GB · 139 tok/s at MXFP4
Mac Studio M4 Max 128GB · 136 tok/s at MXFP4
NVIDIA RTX 4070 Ti Super 16GB · 130 tok/s at MXFP4
AMD RX 7900 XT 20GB · 124 tok/s at MXFP4
AMD RX 9070 XT 16GB · 122 tok/s at MXFP4
NVIDIA RTX 5060 Ti 16GB · 87 tok/s at MXFP4
MacBook Pro M5 Pro 48GB · 82 tok/s at MXFP4
MacBook M3 Max 48GB · 81 tok/s at MXFP4
Intel Arc Pro B70 32GB · 76 tok/s at MXFP4
NVIDIA RTX 4070 12GB · 74 tok/s at MXFP4
AMD Ryzen AI Max+ 395 128GB (Strix Halo) · 74 tok/s at MXFP4
Mac Mini M4 Pro 64GB · 68 tok/s at MXFP4
MacBook M4 Pro 24GB · 68 tok/s at MXFP4
NVIDIA RTX 3060 12GB · 58 tok/s at MXFP4
NVIDIA DGX Spark 128GB · 53 tok/s at MXFP4
CPU-only (Ryzen 9 9950X, 96GB DDR5) · 29 tok/s at MXFP4
MacBook M2 Pro 16GB · won't run

Other models on the A100 80GB (cloud)

Qwen 3.6/3.8 27B · 49 tok/s at Q4_K_M
GLM-5.3 Flash · won't run
Gemma 4 26B A4B · 329 tok/s at Q4_K_M
Qwen 3.5/3.6 35B A3B · 445 tok/s at Q4_K_M
Ornith 1.5 35B A3B · 350 tok/s at Q4_K_M
DeepSeek V4 Flash · won't run
GPT-OSS 120B · 297 tok/s at MXFP4
Gemma 4 31B · 45 tok/s at Q4_K_M
Llama 3.1 8B · 114 tok/s at Q4_K_M
Qwen 3.5 9B · 112 tok/s at Q4_K_M
DeepSeek R1 Distill 14B · 69 tok/s at Q4_K_M
Ornith 1.5 9B · 110 tok/s at Q4_K_M
Muse Glimmer 30B · 32 tok/s at Q4_K_M
Qwen3 30B A3B · 316 tok/s at Q4_K_M

All models on the A100 80GB (cloud) · GPT-OSS 20B on all hardware

Estimates for a short prompt on a single device. Measured numbers come from community benchmarks (r/LocalLLaMA, localscore.ai and more); others are derived from similar setups or projected from specs. Open source on GitHub.