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Can the Apple M4 Max (64 GB) run OpenHands LM 32B?

77 ptsGreat (A) · 77 of 100 points: Model quality 29.9/45, Memory fit 25.0/25, Speed 10.0/15, Memory use 12.8/15

Yes, it runs well

Runs well. At Q4_K_M it needs about 26.6 GB of 48.0 GB usable, with an estimated speed of 17.6 tok/s.

Best quant
Q4_K_M
Generation speed
17.6 tok/s
Prompt processing
348 tok/s
First token (1K prompt)
2.9 s
Largest safe context
32K

Download OpenHands LM 32B

Recommended for the Apple M4 Max (64 GB): Q4_K_M. Every other quantization has its own download link in the table below.

Quantized files · GGUF

Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.

Download the Q4_K_M file (opens in a new tab)

huggingface.co/lmstudio-community/openhands-lm-32b-v0.1-GGUF (opens in a new tab)

ollama run hf.co/lmstudio-community/openhands-lm-32b-v0.1-GGUF:Q4_K_M

Original weights · Hugging Face

Full-precision files from All Hands AI, for fine-tuning, vLLM, Transformers.

huggingface.co/OpenHands/openhands-lm-32b-v0.1 (opens in a new tab)

No sign-in needed.

How the A grade is scored

Every result gets up to 100 points from four parts. The points decide the letter grade.

Model qualityEditorial quality tier of the model, scaled by the quantization or precision used.29.9 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.25.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.10.0 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.12.8 / 15
Total77.7 / 10077 ptsGreat (A) · 77 of 100 points: Model quality 29.9/45, Memory fit 25.0/25, Speed 10.0/15, Memory use 12.8/15

Grade scale: S 85+ · A 72+ · B 58+ · C 42+ · D 25+ · F under 25 points.

Every quantization on the Apple M4 Max (64 GB)

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 19.7 GB 48.0 GB 28.9 tok/s Runs well 69 ptsGood (B) · 69 of 100 points: Model quality 22.1/45, Memory fit 25.0/25, Speed 12.8/15, Memory use 9.5/15 GGUF files (opens in a new tab)
Q3_K_M 22.6 GB 48.0 GB 22.8 tok/s Runs well 73 ptsGreat (A) · 73 of 100 points: Model quality 26.5/45, Memory fit 25.0/25, Speed 11.3/15, Memory use 10.9/15 GGUF (Q3_K_L) (opens in a new tab)
Q4_K_M 26.6 GB 48.0 GB 17.6 tok/s Runs well 77 ptsGreat (A) · 77 of 100 points: Model quality 29.9/45, Memory fit 25.0/25, Speed 10.0/15, Memory use 12.8/15 GGUF (opens in a new tab)
Q5_K_M 29.8 GB 48.0 GB 14.6 tok/s Runs well 78 ptsGreat (A) · 78 of 100 points: Model quality 30.6/45, Memory fit 25.0/25, Speed 9.0/15, Memory use 14.3/15 GGUF files (opens in a new tab)
Q6_K 33.5 GB 48.0 GB 12.2 tok/s Runs well 79 ptsGreat (A) · 79 of 100 points: Model quality 31.2/45, Memory fit 25.0/25, Speed 8.3/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q8_0 41.3 GB 48.0 GB 9.0 tok/s Tight fit 77 ptsGreat (A) · 77 of 100 points: Model quality 31.5/45, Memory fit 24.0/25, Speed 7.1/15, Memory use 15.0/15 GGUF (opens in a new tab)
F16 72.1 GB 48.0 GB — Won't run 9 ptsWon't run (F) · 9 of 100 points: Model quality 9.5/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 Original weights (opens in a new tab)

Memory figures assume 8K of context. Longer conversations or documents grow the KV cache.

Other hardware that runs it

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.