How fast will Qwen 3.6/3.8 27B feel on your hardware?

Qwen 3.6/3.8 27B speed on GPUs and Macs

Qwen 3.6/3.8 27B is a 27.78B-parameter model. Smaller quantizations need less memory and run faster, at some cost in quality. Below is the expected speed on each piece of hardware at the best quantization that fits.

HardwareQuantizationMemoryGenerationFirst token
H200 141GB (cloud)Q4_K_MFits115 tok/s0.3 s
H100 80GB (cloud)Q4_K_MFits80 tok/s0.3 s
A100 80GB (cloud)Q4_K_MFits49 tok/s0.3 s
NVIDIA RTX 5090 32GBQ4_K_MFits43 tok/s0.3 s
NVIDIA RTX PRO 6000 96GBQ4_K_MFits43 tok/s0.3 s
AMD RX 7900 XTX 24GBQ4_K_MFits36 tok/s0.4 s
Mac Studio M5 Ultra 512GBQ4_K_MFits34 tok/s0.4 s
AMD RX 7900 XT 20GBQ4_K_MFits30 tok/s0.5 s
Mac Studio M3 Ultra 512GBQ4_K_MFits25 tok/s0.4 s
NVIDIA RTX 4090 24GBQ4_K_MFits24 tok/s0.3 s
AMD Radeon AI PRO R9700 32GBQ4_K_MFits24 tok/s0.4 s
NVIDIA RTX 3090 24GBQ4_K_MFits22 tok/s0.3 s
MacBook Pro M5 Max 128GBQ4_K_MFits19 tok/s0.4 s
Mac Studio M4 Max 128GBQ4_K_MFits17 tok/s0.5 s
AMD RX 9070 XT 16GBQ4_K_MPartial offload14 tok/s1.4 s
NVIDIA RTX 5080 16GBQ4_K_MPartial offload13 tok/s1.3 s
MacBook M3 Max 48GBQ4_K_MFits12 tok/s0.6 s
NVIDIA RTX 5070 Ti 16GBQ4_K_MPartial offload12 tok/s1.3 s
NVIDIA RTX 4070 Ti Super 16GBQ4_K_MPartial offload10 tok/s1.3 s
AMD Ryzen AI Max+ 395 128GB (Strix Halo)Q4_K_MFits9.5 tok/s0.6 s
MacBook Pro M5 Pro 48GBQ4_K_MFits9.5 tok/s0.5 s
Mac Mini M4 Pro 64GBQ4_K_MFits8.4 tok/s0.7 s
MacBook M4 Pro 24GBQ4_K_MFits8.4 tok/s0.7 s
NVIDIA RTX 5060 Ti 16GBQ4_K_MPartial offload8.2 tok/s1.4 s
Intel Arc Pro B70 32GBQ4_K_MFits7.5 tok/s0.6 s
NVIDIA DGX Spark 128GBQ4_K_MFits6.5 tok/s0.3 s
NVIDIA RTX 4070 12GBQ4_K_MPartial offload6.5 tok/s1.3 s
NVIDIA RTX 3060 12GBQ4_K_MPartial offload5.7 tok/s1.5 s
CPU-only (Ryzen 9 9950X, 96GB DDR5)Q4_K_MFits3.6 tok/s0.9 s
MacBook M2 Pro 16GBQ4_K_MDoesn't fitWon't run—

Other models

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.