Run GLM-5.3 on M3 Ultra

The LLMCheck index estimates GLM-5.3 at ~11 tok/s on an M3 Ultra at Q4_K_M, a figure from its published bandwidth model, not a measured run. It needs about 256 GB of unified memory. It is Zhipu AI's 753B mixture-of-experts model (40B active), released under the GLM-5.3 licence.

Speed
estimated~11
tok/s
First Token
—
seconds
RAM Needed
256
GB minimum
Engine
MLX
of this figure
Want to run GLM-5.3 faster — or step up to bigger models? Find your Mac →

The figure

This is an LLMCheck index estimate from its published two-term bandwidth model, not a measured run; the index labels it so everywhere it appears. Own this Mac? Submit a real run →

MetricValue
Tokens per secondestimated~11 tok/s
Provenanceestimate · how estimates are made
QuantizationQ4_K_M
EngineMLX
Figure dated2026-09
Minimum RAM256 GB
Parameters753B MoE (40B active)
Chip bandwidth819 GB/s

Every figure for GLM-5.3 on the M3 Ultra

Each row as the index holds it, with its source. “Mac RAM” is the memory of the Mac a run used, not the model’s requirement (256 GB). The headline figure follows the reference rule: the lower-median measured plain-decode run at 5 bits or fewer (a run whose quant was not stated counts only when no stated-quant run qualifies), else the estimate; a run marked “not used to anchor estimates” is listed here but never becomes the headline.

SpeedQuantEngineMac RAMContextSourceNote
estimated19 tok/sQ2_KMLX256 GB—LLMCheck estimator—
estimated11 tok/sQ4_K_MMLX512 GB—LLMCheck estimator—
Provenance key
sourced
Published figure — vendor or press review
estimated
community
Linked individual run — blog, forum or submission

Setup: run GLM-5.3 on a Mac

Ollama — the index has not verified an Ollama tag for GLM-5.3, so it doesn’t print one (a guessed tag fails with “pull model manifest: file does not exist”). Search the Ollama library →

MLX — pick a build from Hugging Face’s MLX listings, then run it with its repo id:

pip install -U mlx-lm
mlx_lm.generate --model <repo-id> --prompt "Hello"

Downloads: Search the Ollama library → · model card →

Prefer a GUI? LM Studio downloads GGUF and MLX builds in one click. Step by step: install Ollama on a Mac.

GLM-5.3 on other Apple Silicon chips

ChipSpeedQuantEngineBandwidth
M5 Ultraestimated17 tok/sQ4_K_MMLX1228 GB/s

About GLM-5.3

Zhipu's post-training upgrade of GLM 5.2 on the same 753B MoE base (~40B active): Terminal-Bench 2.1 88.2, DeepSWE v1.1 66.9 (model card). Released 14 August; weights public 25 August 2026 under the custom GLM-5.3 License — MIT-like for everyone except model-as-a-service operators above US$10B revenue, who need Z.AI's security review. 2-bit is 239 GB, so it starts at a 256 GB Mac Studio (roughly 27 tok/s there); at 4-bit it needs the 512 GB model, ~17 tok/s estimated on M5 Ultra. Where GLM 5.2 stays MIT, 5.3 does not.

GLM-5.3 licence · 753B MoE · 1000K context · LLMCheck capability 50/50 · see its leaderboard rank →

System requirements

Macs with the M3 Ultra

🛒 Get a Mac that runs GLM-5.3

GLM-5.3 needs about 256 GB of unified memory. These current Apple Silicon Macs have the headroom to run it comfortably:

As an Amazon Associate, LLMCheck earns from qualifying purchases. These affiliate links cost you nothing extra and help keep the LLMCheck index free.

Compare More Models

See how GLM-5.3 stacks up against other models on your specific Mac hardware.

Open Compare Tool Full Leaderboard