How fast will GLM-5.3 feel on your hardware?

GLM-5.3 speed on GPUs and Macs

GLM-5.3 is a 753.33B-parameter mixture-of-experts model (39B 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 512GBUD-IQ4_XSFits31 tok/s0.4 s
Mac Studio M3 Ultra 512GBUD-IQ4_XSFits21 tok/s0.5 s
AMD Ryzen AI Max+ PRO 495 192GB (Gorgon Halo)UD-IQ1_SPartial offload11 tok/s2.1 s
AMD Ryzen AI Max+ 395 128GB (Strix Halo)UD-IQ1_SPartial offload7.0 tok/s2.1 s
NVIDIA RTX Spark N1X 128GB (laptop)UD-IQ1_SPartial offload6.6 tok/s1.3 s
NVIDIA DGX Spark 128GBUD-IQ1_SPartial offload6.4 tok/s1.3 s
NVIDIA RTX 3090 24GBUD-IQ1_SDoesn't fitWon't run—
NVIDIA RTX 5090 32GBUD-IQ1_SDoesn't fitWon't run—
AMD Radeon AI PRO R9700 32GBUD-IQ1_SDoesn't fitWon't run—
NVIDIA RTX 4090 24GBUD-IQ1_SDoesn't fitWon't run—
Mac Studio M5 Ultra 256GBUD-IQ1_SDoesn't fitWon't run—
MacBook Pro M5 Max 128GBUD-IQ1_SDoesn't fitWon't run—
NVIDIA RTX 5060 Ti 16GBUD-IQ1_SDoesn't fitWon't run—
NVIDIA RTX PRO 6000 96GBUD-IQ1_SDoesn't fitWon't run—
NVIDIA Tesla V100 32GBUD-IQ1_SDoesn't fitWon't run—
Intel Arc Pro B70 32GBUD-IQ1_SDoesn't fitWon't run—
AMD RX 7900 XTX 24GBUD-IQ1_SDoesn't fitWon't run—
NVIDIA RTX 5070 Ti 16GBUD-IQ1_SDoesn't fitWon't run—
NVIDIA RTX 3060 12GBUD-IQ1_SDoesn't fitWon't run—
NVIDIA RTX 5080 16GBUD-IQ1_SDoesn't fitWon't run—
Mac mini M5 Pro 64GBUD-IQ1_SDoesn't fitWon't run—
AMD Instinct MI50 32GBUD-IQ1_SDoesn't fitWon't run—
MacBook Pro M5 Pro 48GBUD-IQ1_SDoesn't fitWon't run—
Mac Studio M4 Max 128GBUD-IQ1_SDoesn't fitWon't run—
AMD RX 9070 XT 16GBUD-IQ1_SDoesn't fitWon't run—
AMD RX 7900 XT 20GBUD-IQ1_SDoesn't fitWon't run—
CPU-only (Ryzen 9 9950X, 96GB DDR5)UD-IQ1_SDoesn't fitWon't run—
MacBook M4 Pro 24GBUD-IQ1_SDoesn't fitWon't run—
H100 80GB (cloud)UD-IQ1_SDoesn't fitWon't run—
H200 141GB (cloud)UD-IQ1_SDoesn'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.