How fast will local models feel on the A100 80GB (cloud)?

Local LLM speed on the A100 80GB (cloud)

The A100 80GB (cloud) has 80 GB of memory and 2039 GB/s of memory bandwidth, which is what mostly decides generation speed. Below is the expected speed for each model at the best quantization that fits.

Model	Quantization	Memory	Generation	First token
Qwen 3.6/3.8 27B	Q4_K_M	Fits	49 tok/s	0.3 s
GLM-5.3 Flash	UD-IQ1_S	Doesn't fit	Won't run	—
GPT-OSS 20B	MXFP4	Fits	394 tok/s	0.3 s
Gemma 4 26B A4B	Q4_K_M	Fits	329 tok/s	0.3 s
Qwen 3.5/3.6 35B A3B	Q4_K_M	Fits	445 tok/s	0.3 s
Ornith 1.5 35B A3B	Q4_K_M	Fits	350 tok/s	0.3 s
DeepSeek V4 Flash	UD-IQ1_S	Doesn't fit	Won't run	—
GPT-OSS 120B	MXFP4	Fits	297 tok/s	0.3 s
Gemma 4 31B	Q4_K_M	Fits	45 tok/s	0.3 s
Llama 3.1 8B	Q4_K_M	Fits	114 tok/s	0.3 s
Qwen 3.5 9B	Q4_K_M	Fits	112 tok/s	0.3 s
DeepSeek R1 Distill 14B	Q4_K_M	Fits	69 tok/s	0.3 s
Ornith 1.5 9B	Q4_K_M	Fits	110 tok/s	0.3 s
Muse Glimmer 30B	Q4_K_M	Fits	32 tok/s	0.3 s
Qwen3 30B A3B	Q4_K_M	Fits	316 tok/s	0.3 s

Other 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.