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Can the Apple M2 Pro (32 GB) run Ling Mini 2.0 (16B-A1.4B)?

78 ptsGreat (A) · 78 of 100 points: Model quality 23.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15

Yes, it runs well

Runs well. At Q6_K it needs about 16.0 GB of 21.4 GB usable, with an estimated speed of 52.4 tok/s.

Best quant
Q6_K
Generation speed
52.4 tok/s
Prompt processing
3,011 tok/s
First token (1K prompt)
0.3 s
Largest safe context
32K

Download Ling Mini 2.0 (16B-A1.4B)

Recommended for the Apple M2 Pro (32 GB): Q6_K. 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 Q6_K file (opens in a new tab)

huggingface.co/inclusionAI/Ling-mini-2.0-GGUF (opens in a new tab)

ollama run hf.co/inclusionAI/Ling-mini-2.0-GGUF:Q6_K

Original weights · Hugging Face

Full-precision files from Ant Group (inclusionAI), for fine-tuning, vLLM, Transformers.

huggingface.co/inclusionAI/Ling-mini-2.0 (opens in a new tab)

No sign-in needed.

Official repo · GitHub

Reference code, inference scripts and docs from Ant Group (inclusionAI). The weights themselves download from Hugging Face.

github.com/inclusionAI/Ling-V2 (opens in a new tab)

git clone https://github.com/inclusionAI/Ling-V2

Links checked 6 days ago against Hugging Face, Ollama and GitHub.

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.23.2 / 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.15.0 / 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
Total78.2 / 10078 ptsGreat (A) · 78 of 100 points: Model quality 23.2/45, Memory fit 25.0/25, Speed 15.0/15, 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 9.2 GB 21.4 GB 124 tok/s Runs well 66 ptsGood (B) · 66 of 100 points: Model quality 16.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 9.9/15 GGUF (opens in a new tab)
Q3_K_M 10.6 GB 21.4 GB 97.6 tok/s Runs well 71 ptsGood (B) · 71 of 100 points: Model quality 19.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 11.4/15 GGUF files (opens in a new tab)
Q4_K_M 12.6 GB 21.4 GB 75.5 tok/s Runs well 75 ptsGreat (A) · 75 of 100 points: Model quality 22.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 13.5/15 GGUF (opens in a new tab)
Q5_K_M 14.2 GB 21.4 GB 62.4 tok/s Runs well 77 ptsGreat (A) · 77 of 100 points: Model quality 22.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF files (opens in a new tab)
Q6_K 16.0 GB 21.4 GB 52.4 tok/s Runs well 78 ptsGreat (A) · 78 of 100 points: Model quality 23.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q8_0 19.9 GB 21.4 GB 38.4 tok/s Tight fit 77 ptsGreat (A) · 77 of 100 points: Model quality 23.4/45, Memory fit 24.0/25, Speed 14.7/15, Memory use 15.0/15 GGUF (opens in a new tab)
F16 35.2 GB 21.4 GB — Won't run 7 ptsWon't run (F) · 7 of 100 points: Model quality 7.0/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF (opens in a new tab) 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.