InternLM2 Math Plus 20B on Apple M2 (8 GB)

Can the Apple M2 (8 GB) run InternLM2 Math Plus 20B?

3 pts

No, it doesn’t fit

No. InternLM2 Math Plus 20B needs about 10.6 GB even at Q2_K; the Apple M2 (8 GB) has 5.4 GB usable.

Download InternLM2 Math Plus 20B

Recommended: Q2_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 Q2_K file (opens in a new tab)

huggingface.co/bartowski/internlm2-math-plus-20b-GGUF (opens in a new tab)

ollama run hf.co/bartowski/internlm2-math-plus-20b-GGUF:Q2_K

Original weights · Hugging Face

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

huggingface.co/internlm/internlm2-math-plus-20b (opens in a new tab)

No sign-in needed.

Links checked 5 days ago against Hugging Face, Ollama and GitHub.

How the F 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.	3.8 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.	0.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.	0.0 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.	0.0 / 15
Total	3.8 / 100	3 ptsWon't run (F) · 3 of 100 points: Model quality 3.8/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15

It doesn’t fit, so only a reduced share of the quality points counts and fit, speed and memory use score zero.

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

Every quantization on the Apple M2 (8 GB)

Quant	Memory needed	Available	Speed	Fit	Grade · points	Download
`Q2_K`	10.6 GB	5.4 GB	—	Won't run	3 ptsWon't run (F) · 3 of 100 points: Model quality 3.8/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	GGUF (opens in a new tab)
`Q3_K_M`	12.4 GB	5.4 GB	—	Won't run	4 ptsWon't run (F) · 4 of 100 points: Model quality 4.5/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	GGUF (opens in a new tab)
`Q4_K_M`	14.8 GB	5.4 GB	—	Won't run	5 ptsWon't run (F) · 5 of 100 points: Model quality 5.1/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	GGUF (opens in a new tab)
`Q5_K_M`	16.7 GB	5.4 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`	18.9 GB	5.4 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`	23.7 GB	5.4 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	GGUF (opens in a new tab)
`F16`	42.4 GB	5.4 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 8K of context. Longer conversations or documents grow the KV cache.

Hardware that can run it

73 ptsGreat (A) · 73 of 100 points: Model quality 18.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 5090 Q8_0 · 56.4 tok/s
72 ptsGreat (A) · 72 of 100 points: Model quality 17.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 3090 Q6_K · 40.1 tok/s
72 ptsGreat (A) · 72 of 100 points: Model quality 17.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 4090 Q6_K · 43.2 tok/s
72 ptsGreat (A) · 72 of 100 points: Model quality 17.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 AMD Radeon RX 7900 XTX Q5_K_M · 42.2 tok/s
71 ptsGood (B) · 71 of 100 points: Model quality 17.1/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 4070 Ti SUPER Q4_K_M · 41.5 tok/s
71 ptsGood (B) · 71 of 100 points: Model quality 17.1/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 4080 SUPER Q4_K_M · 45.5 tok/s

Models that do run on the Apple M2 (8 GB)

77 ptsGreat (A) · 77 of 100 points: Model quality 26.1/45, Memory fit 25.0/25, Speed 11.9/15, Memory use 15.0/15 TMax 4B Q4_K_M · 25.1 tok/s
77 ptsGreat (A) · 77 of 100 points: Model quality 26.5/45, Memory fit 25.0/25, Speed 11.3/15, Memory use 15.0/15 Qwen3.5 4B Q4_K_M · 22.7 tok/s
77 ptsGreat (A) · 77 of 100 points: Model quality 26.5/45, Memory fit 25.0/25, Speed 10.8/15, Memory use 15.0/15 Gemma 4 E2B Q4_K_M · 20.6 tok/s
77 ptsGreat (A) · 77 of 100 points: Model quality 25.7/45, Memory fit 25.0/25, Speed 11.4/15, Memory use 15.0/15 Agents-A1 4B Q4_K_M · 23.3 tok/s
76 ptsGreat (A) · 76 of 100 points: Model quality 22.7/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 Ling 3.0 Tiny (8B-A1.3B) Q3_K_M · 52.6 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.