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Can the Apple M2 Pro (32 GB) run Yi 34B Chat?

60 ptsGood (B) · 60 of 100 points: Model quality 15.1/45, Memory fit 24.0/25, Speed 6.7/15, Memory use 15.0/15

Yes, with little memory to spare

Tight fit. At Q3_K_M it needs about 20.2 GB of 21.4 GB usable, with an estimated speed of 7.9 tok/s.

Best quant
Q3_K_M
Generation speed
7.9 tok/s
Prompt processing
123 tok/s
First token (1K prompt)
8.4 s
Largest safe context
4K

Download Yi 34B Chat

Recommended for the Apple M2 Pro (32 GB): Q3_K_M. Every other quantization has its own download link in the table below.

Quickest · Ollama

One command downloads a ready-to-run version and starts a chat.

ollama run yi:34b-chat-q3_K_M

Get Ollama at ollama.com/download (opens in a new tab) · model page (opens in a new tab)

Quantized files · GGUF

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

Download the Q3_K_M file (opens in a new tab)

huggingface.co/mradermacher/Yi-34B-Chat-i1-GGUF (opens in a new tab)

ollama run hf.co/mradermacher/Yi-34B-Chat-i1-GGUF:Q3_K_M

Original weights · Hugging Face

Full-precision files from 01.AI, for fine-tuning, vLLM, Transformers.

huggingface.co/01-ai/Yi-34B-Chat (opens in a new tab)

No sign-in needed.

How the B 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.15.1 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.24.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.6.7 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.15.0 / 15
Total60.8 / 10060 ptsGood (B) · 60 of 100 points: Model quality 15.1/45, Memory fit 24.0/25, Speed 6.7/15, Memory use 15.0/15

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

Every quantization on the Apple M2 Pro (32 GB)

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 17.1 GB 21.4 GB 10.1 tok/s Runs well 60 ptsGood (B) · 60 of 100 points: Model quality 12.6/45, Memory fit 25.0/25, Speed 7.5/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q3_K_M 20.2 GB 21.4 GB 7.9 tok/s Tight fit 60 ptsGood (B) · 60 of 100 points: Model quality 15.1/45, Memory fit 24.0/25, Speed 6.7/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q4_K_M 24.3 GB 21.4 GB 5.2 tok/s Heavy offload 41 ptsPoor (D) · 41 of 100 points: Model quality 17.1/45, Memory fit 4.0/25, Speed 5.4/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q5_K_M 27.7 GB 21.4 GB — Won't run 5 ptsWon't run (F) · 5 of 100 points: Model quality 5.2/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF (opens in a new tab)
Q6_K 31.5 GB 21.4 GB — Won't run 5 ptsWon't run (F) · 5 of 100 points: Model quality 5.3/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF (opens in a new tab)
Q8_0 39.8 GB 21.4 GB — Won't run 5 ptsWon't run (F) · 5 of 100 points: Model quality 5.4/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15
F16 72.1 GB 21.4 GB — Won't run 5 ptsWon't run (F) · 5 of 100 points: Model quality 5.4/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 Original weights (opens in a new tab)

Memory figures assume 4K 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.