What LLMs Can the Apple M5 Max 128GB Run?

The Apple M5 Max 128GB has 128 GB of unified memory (about 96.0 GB usable by the GPU) and 614 GB/s of bandwidth. It runs 50 of 58 models fully at Q4_K_M with 8K context, up to Qwen 3.5 122B-A10B, and generates about 72 tokens/s on an 8B model.

Apple · Apple Silicon · Released 2026-03 · Updated October 14, 2026

51 of 58 models fit

Apple M5 Max 128GB (96.0 GB GPU-usable) at Q4_K_M with 8K context. Largest that fits fully: Qwen 3.5 122B-A10B.

ModelNeedsStatusSpeedBest quant that fits
Qwen 3.5 122B-A10B70.2 GBFits~48 tok/sQ5_K_M
Mistral Small 4 119B68.2 GBFits~73 tok/sQ5_K_M
gpt-oss-120b67.2 GBFits~85 tok/sMXFP4 (official)
Llama 4 Scout64.0 GBFits~31 tok/sQ6_K
GLM-4.5-Air62.1 GBFits~40 tok/sQ6_K
Qwen3-Next 80B-A3B46.3 GBFits~102 tok/sQ8_0
Qwen 2.5 72B44.5 GBFits~8.7 tok/sQ8_0
Llama 3.3 70B43.2 GBFits~9.0 tok/sQ8_0
DeepSeek R1 Distill Llama 70B43.2 GBFits~9.0 tok/sQ8_0
Mixtral 8x7B28.0 GBFits~41 tok/sFP16 / BF16
Qwen 2.5 32B21.4 GBFits~19 tok/sFP16 / BF16
Qwen 2.5 Coder 32B21.4 GBFits~19 tok/sFP16 / BF16
DeepSeek R1 Distill Qwen 32B21.4 GBFits~19 tok/sFP16 / BF16
Qwen 3 32B21.4 GBFits~19 tok/sFP16 / BF16
Qwen 3.5 35B-A3B21.0 GBFits~112 tok/sFP16 / BF16
Qwen 3.6 35B-A3B21.0 GBFits~112 tok/sFP16 / BF16
Gemma 4 31B19.8 GBFits~20 tok/sFP16 / BF16
Qwen 3 30B-A3B18.8 GBFits~92 tok/sFP16 / BF16
Qwen3-Coder 30B-A3B18.8 GBFits~92 tok/sFP16 / BF16
Gemma 3 27B17.6 GBFits~23 tok/sFP16 / BF16
Qwen 3.5 27B16.9 GBFits~23 tok/sFP16 / BF16
Qwen 3.6 27B16.9 GBFits~23 tok/sFP16 / BF16
Qwen 3.8 27B16.9 GBFits~23 tok/sFP16 / BF16
Mistral Small 3.1 24B15.6 GBFits~26 tok/sFP16 / BF16
Gemma 4 26B-A4B15.6 GBFits~105 tok/sFP16 / BF16
gpt-oss-20b12.9 GBFits~123 tok/sMXFP4 (official)
Qwen 2.5 14B10.7 GBFits~40 tok/sFP16 / BF16
DeepSeek R1 Distill Qwen 14B10.7 GBFits~40 tok/sFP16 / BF16
Phi-4 14B10.6 GBFits~40 tok/sFP16 / BF16
Qwen 3 14B10.5 GBFits~41 tok/sFP16 / BF16
Ministral 3 14B9.7 GBFits~44 tok/sFP16 / BF16
Mistral Nemo 12B9.0 GBFits~49 tok/sFP16 / BF16
Gemma 3 12B8.8 GBFits~49 tok/sFP16 / BF16
Ministral 3 8B6.7 GBFits~68 tok/sFP16 / BF16
Qwen 3 8B6.6 GBFits~70 tok/sFP16 / BF16
Qwen 3.5 9B6.4 GBFits~70 tok/sFP16 / BF16
Llama 3.1 8B6.3 GBFits~72 tok/sFP16 / BF16
DeepSeek R1 Distill Llama 8B6.3 GBFits~72 tok/sFP16 / BF16
Mistral 7B v0.35.7 GBFits~79 tok/sFP16 / BF16
Gemma 4 E4B5.7 GBFits~78 tok/sFP16 / BF16
Qwen 2.5 7B5.6 GBFits~80 tok/sFP16 / BF16
DeepSeek R1 Distill Qwen 7B5.6 GBFits~80 tok/sFP16 / BF16
Qwen 3 4B4.2 GBFits~125 tok/sFP16 / BF16
Phi-4 Mini4.1 GBFits~133 tok/sFP16 / BF16
Gemma 4 E2B4.0 GBFits~122 tok/sFP16 / BF16
Gemma 3 4B3.7 GBFits~135 tok/sFP16 / BF16
Qwen 3.5 4B3.7 GBFits~140 tok/sFP16 / BF16
Ministral 3 3B3.5 GBFits~152 tok/sFP16 / BF16
Llama 3.2 3B3.5 GBFits~158 tok/sFP16 / BF16
Llama 3.2 1B1.7 GBFits~420 tok/sFP16 / BF16
Gemma 3 1B1.6 GBFits~541 tok/sFP16 / BF16
Kimi K2.6566 GBToo small––
DeepSeek R1 671B380 GBToo small––
Llama 3.1 405B234 GBToo small––
Qwen 3.5 397B-A17B226 GBToo small––
DeepSeek V4 Flash161 GBToo small––
Qwen 3 235B-A22B135 GBToo small–Q2_K
MiniMax-M2133 GBToo small–Q2_K

Apple M5 Max 128GB for local AI

The 40-core M5 Max with 614 GB/s, about 12% more bandwidth than the M4 Max and much faster prompt processing thanks to the GPU neural accelerators. About 96 GB is GPU-usable by default.

Among the 5 devices we track with about 96 GB of usable memory, the Apple M5 Max 128GB ranks 2 of 5 for text-generation speed, because generation speed follows memory bandwidth. Others in the same class: RTX PRO 6000 Blackwell 96GB, Apple M4 Max 128GB, Apple M3 Max 128GB, Ryzen AI Max+ 395 128GB. They all hold the same models; the faster ones simply answer sooner.

Our picks for the Apple M5 Max 128GB

The model we would run first for each job, chosen from our recommendations by what fits fully with an 8K context. "Best quant" is the highest quality that fits; "max context" is at Q4_K_M or the native format.

TaskModelBest quantMax contextSpeed
Best all-rounderQwen 3.5 122B-A10BQ5_K_M256K~48 tok/s
CodingGLM-4.5-AirQ6_K128K~40 tok/s
Fastest repliesQwen 3.5 122B-A10BQ5_K_M256K~48 tok/s
Long documents (64K+)Qwen 3.5 122B-A10BQ5_K_M256K~48 tok/s
Images in, text outGemma 4 31BFP16 / BF16256K~20 tok/s
Image generationFLUX.2 [dev]FP8––
SpecValue
Memory128 GB unified (96.0 GB GPU-usable by default)
Memory bandwidth614 GB/s
ArchitectureApple Silicon
Released2026-03
Llama 3.1 8B Q4_K_M speed~72 tok/s
Largest model that fitsQwen 3.5 122B-A10B

Image and video models on the Apple M5 Max 128GB

Peak VRAM with model swapping (ComfyUI default on smaller cards).

ModelFP8FP8 fitGGUF Q4Q4 fit
Stable Diffusion 1.51.8 GBFits1.7 GBFits
SDXL 1.04.1 GBFits4.1 GBFits
Stable Diffusion 3.5 Medium6.4 GBFits6.4 GBFits
Stable Diffusion 3.5 Large8.6 GBFits6.4 GBFits
FLUX.1 [dev]12.1 GBFits7.3 GBFits
FLUX.1 [schnell]12.1 GBFits7.3 GBFits
Qwen-Image20.4 GBFits12.3 GBFits
Wan 2.2 A14B (T2V / I2V)18.8 GBFits13.2 GBFits
Wan 2.2 TI2V 5B8.0 GBFits6.5 GBFits
HunyuanVideo18.3 GBFits13.1 GBFits
FLUX.1 Kontext [dev]12.3 GBFits7.5 GBFits
FLUX.2 [dev]31.0 GBFits23.6 GBFits
Z-Image Turbo6.8 GBFits4.9 GBFits
Qwen-Image-Edit 250920.5 GBFits12.4 GBFits
LTX-219.2 GBFits12.6 GBFits

Upgrade path

The next step up is the Apple M2 Ultra 192GB with 192 GB and 30% more bandwidth.

Comparisons

Apple M5 Max 128GB for LLMs: common questions

Can the Apple M5 Max 128GB run Llama 3.3 70B?

Yes. Llama 3.3 70B needs about 43.2 GB at Q4_K_M with 8K context, and the best quality that fits is Q8_0.

Can the Apple M5 Max 128GB run Qwen 3 32B?

Yes. Qwen 3 32B needs about 21.4 GB at Q4_K_M with 8K context, and the best quality that fits is FP16 / BF16.

Can the Apple M5 Max 128GB run Qwen 3 14B?

Yes. Qwen 3 14B needs about 10.5 GB at Q4_K_M with 8K context, and the best quality that fits is FP16 / BF16.

How fast is the Apple M5 Max 128GB for LLMs?

About 72 tokens per second for an 8B model at Q4_K_M, based on its 614 GB/s memory bandwidth. Larger models scale down roughly in proportion to their size.

How much of the 128 GB can the GPU use?

About 96.0 GB by default. You can raise it with sudo sysctl iogpu.wired_limit_mb=<MB> (resets on reboot), leaving at least 8 GB for macOS.

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