Granite Code 20B Instruct on Apple M2 Pro (32 GB)

Can the Apple M2 Pro (32 GB) run Granite Code 20B Instruct?

63 pts

Yes, it runs well

Runs well. At Q4_K_M it needs about 14.8 GB of 21.4 GB usable, with an estimated speed of 10.5 tok/s.

Best quant: Q4_K_M
Generation speed: 10.5 tok/s
Prompt processing: 210 tok/s
First token (1K prompt): 4.9 s
Largest safe context: 8K

Download Granite Code 20B Instruct

Recommended for the Apple M2 Pro (32 GB): Q4_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 granite-code:20b-instruct-8k-q4_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 Q4_K_M file (opens in a new tab)

huggingface.co/ibm-granite/granite-20b-code-instruct-8k-GGUF (opens in a new tab)

ollama run hf.co/ibm-granite/granite-20b-code-instruct-8k-GGUF:Q4_K_M

Original weights · Hugging Face

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

huggingface.co/ibm-granite/granite-20b-code-instruct-8k (opens in a new tab)

No sign-in needed.

Links checked 1 week ago against Hugging Face, Ollama and GitHub.

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.	15.4 / 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.	7.7 / 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
Total	63.1 / 100	63 ptsGood (B) · 63 of 100 points: Model quality 15.4/45, Memory fit 25.0/25, Speed 7.7/15, 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`	10.6 GB	21.4 GB	17.3 tok/s	Runs well	57 ptsUsable (C) · 57 of 100 points: Model quality 11.3/45, Memory fit 25.0/25, Speed 9.9/15, Memory use 11.4/15
`Q3_K_M`	12.4 GB	21.4 GB	13.6 tok/s	Runs well	60 ptsGood (B) · 60 of 100 points: Model quality 13.6/45, Memory fit 25.0/25, Speed 8.8/15, Memory use 13.3/15
`Q4_K_M`	14.8 GB	21.4 GB	10.5 tok/s	Runs well	63 ptsGood (B) · 63 of 100 points: Model quality 15.4/45, Memory fit 25.0/25, Speed 7.7/15, Memory use 15.0/15	GGUF (opens in a new tab)
`Q5_K_M`	16.8 GB	21.4 GB	8.7 tok/s	Runs well	62 ptsGood (B) · 62 of 100 points: Model quality 15.7/45, Memory fit 25.0/25, Speed 7.0/15, Memory use 15.0/15
`Q6_K`	19.0 GB	21.4 GB	7.3 tok/s	Tight fit	61 ptsGood (B) · 61 of 100 points: Model quality 16.0/45, Memory fit 24.0/25, Speed 6.4/15, Memory use 15.0/15
`Q8_0`	23.8 GB	21.4 GB	4.6 tok/s	Heavy offload	40 ptsPoor (D) · 40 of 100 points: Model quality 16.2/45, Memory fit 4.0/25, Speed 5.1/15, Memory use 15.0/15
`F16`	42.7 GB	21.4 GB	—	Won't run	4 ptsWon't run (F) · 4 of 100 points: Model quality 4.9/45, 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

71 ptsGood (B) · 71 of 100 points: Model quality 16.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 5090 Q8_0 · 55.8 tok/s
71 ptsGood (B) · 71 of 100 points: Model quality 16.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 4090 Q6_K · 42.8 tok/s
70 ptsGood (B) · 70 of 100 points: Model quality 16.0/45, Memory fit 25.0/25, Speed 14.9/15, Memory use 15.0/15 NVIDIA GeForce RTX 3090 Q6_K · 39.7 tok/s
70 ptsGood (B) · 70 of 100 points: Model quality 15.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 AMD Radeon RX 7900 XTX Q5_K_M · 41.8 tok/s
69 ptsGood (B) · 69 of 100 points: Model quality 15.7/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 5070 Ti Q5_K_M · 45.3 tok/s
69 ptsGood (B) · 69 of 100 points: Model quality 15.7/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 5080 Q5_K_M · 48.5 tok/s

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.