How fast will DeepSeek V4.1 Flash feel on your hardware?

DeepSeek V4.1 Flash speed on GPUs and Macs

DeepSeek V4.1 Flash is a 748.49B-parameter mixture-of-experts model (16B active per token). 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
Mac Studio M5 Ultra 512GBQ3_K_MFits78 tok/s0.3 s
Mac Studio M3 Ultra 512GBQ3_K_MFits53 tok/s0.4 s
AMD Ryzen AI Max+ PRO 495 192GB (Gorgon Halo)Q2_KPartial offload17 tok/s1.6 s
AMD Ryzen AI Max+ 395 128GB (Strix Halo)Q2_KPartial offload12 tok/s1.6 s
NVIDIA RTX Spark N1X 128GB (laptop)Q2_KPartial offload12 tok/s1.2 s
NVIDIA DGX Spark 128GBQ2_KPartial offload12 tok/s1.2 s
NVIDIA RTX 3090 24GBQ2_KDoesn't fitWon't run—
NVIDIA RTX 5090 32GBQ2_KDoesn't fitWon't run—
AMD Radeon AI PRO R9700 32GBQ2_KDoesn't fitWon't run—
NVIDIA RTX 4090 24GBQ2_KDoesn't fitWon't run—
Mac Studio M5 Ultra 256GBQ2_KDoesn't fitWon't run—
MacBook Pro M5 Max 128GBQ2_KDoesn't fitWon't run—
NVIDIA RTX 5060 Ti 16GBQ2_KDoesn't fitWon't run—
NVIDIA RTX PRO 6000 96GBQ2_KDoesn't fitWon't run—
NVIDIA Tesla V100 32GBQ2_KDoesn't fitWon't run—
Intel Arc Pro B70 32GBQ2_KDoesn't fitWon't run—
AMD RX 7900 XTX 24GBQ2_KDoesn't fitWon't run—
NVIDIA RTX 5070 Ti 16GBQ2_KDoesn't fitWon't run—
NVIDIA RTX 3060 12GBQ2_KDoesn't fitWon't run—
NVIDIA RTX 5080 16GBQ2_KDoesn't fitWon't run—
Mac mini M5 Pro 64GBQ2_KDoesn't fitWon't run—
AMD Instinct MI50 32GBQ2_KDoesn't fitWon't run—
MacBook Pro M5 Pro 48GBQ2_KDoesn't fitWon't run—
Mac Studio M4 Max 128GBQ2_KDoesn't fitWon't run—
AMD RX 9070 XT 16GBQ2_KDoesn't fitWon't run—
AMD RX 7900 XT 20GBQ2_KDoesn't fitWon't run—
CPU-only (Ryzen 9 9950X, 96GB DDR5)Q2_KDoesn't fitWon't run—
MacBook M4 Pro 24GBQ2_KDoesn't fitWon't run—
H100 80GB (cloud)Q2_KDoesn't fitWon't run—
H200 141GB (cloud)Q2_KDoesn'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.