The Mac M4 Max (128GB) shares system memory with the GPU; roughly 75% (~96.0GB) is usable for models. Its memory bandwidth is 546 GB/s — the main factor behind local LLM generation speed.
| Model | Best quant | Memory (8K) | Verdict | Speed |
|---|---|---|---|---|
| Qwen3.5 4B Qwen · Lightweight, image input | BF16 | 10.5GB | Comfortable | Usable (35 tok/s) |
| Gemma 4 E4B Gemma · Lightweight for phones/laptops | BF16 | 17.2GB | Comfortable | Usable (20 tok/s) |
| Qwen3 8B Qwen · The go-to 8B | BF16 | 18.6GB | Comfortable | Usable (20 tok/s) |
| Llama 3.1 8B Llama · Classic, many fine-tunes | BF16 | 18.1GB | Comfortable | Usable (20 tok/s) |
| Ministral 3 8B Mistral | BF16 | 20.0GB | Comfortable | Usable (18 tok/s) |
| DeepSeek-R1-0528-Qwen3-8B DeepSeek · Reasoning (thinking) model | BF16 | 18.6GB | Comfortable | Usable (20 tok/s) |
| llm-jp-4 8B thinking Japanese · Japanese-focused (Japan) | BF16 | 19.3GB | Comfortable | Usable (19 tok/s) |
| Qwen3-Swallow 8B Japanese · Japanese-enhanced (Institute of Science Tokyo) | BF16 | 18.6GB | Comfortable | Usable (20 tok/s) |
| Qwen3.5 9B Qwen · Image input | BF16 | 20.6GB | Comfortable | Usable (17 tok/s) |
| Gemma 4 12B Gemma · Mid-size, good multilingual | BF16 | 25.6GB | Comfortable | Slowish (14 tok/s) |
| Ministral 3 14B Mistral | BF16 | 30.5GB | Comfortable | Slowish (12 tok/s) |
| Qwen3 14B Qwen | BF16 | 32.2GB | Comfortable | Slowish (11 tok/s) |
| gpt-oss-20b OpenAI · OpenAI open-weight model (MXFP4) | Q4_K_M (MXFP4) | 13.2GB | Comfortable | Fast (96 tok/s) |
| Devstral Small 2 24B Mistral · Coding | BF16 | 51.0GB | Comfortable | Slowish (6.8 tok/s) |
| Gemma 4 26B-A4B Gemma · Fast MoE | BF16 | 53.7GB | Comfortable | Usable (27 tok/s) |
| Qwen3.8 27B Qwen · Latest generation (Aug 2026) | BF16 | 57.9GB | Comfortable | Slowish (5.9 tok/s) |
| Qwen3-Coder 30B-A3B Qwen · Coding MoE | BF16 | 63.8GB | Comfortable | Usable (32 tok/s) |
| GLM-4.7-Flash GLM · MoE, strong at long context | BF16 | 64.8GB | Comfortable | Usable (35 tok/s) |
| Nemotron 3 Nano 30B-A3B NVIDIA · Mamba hybrid, light long context | BF16 | 65.2GB | Comfortable | Usable (30 tok/s) |
| Gemma 4 31B Gemma · Largest Gemma 4 | BF16 | 66.0GB | Comfortable | Slowish (5.2 tok/s) |
| Qwen3 32B Qwen | BF16 | 69.7GB | Comfortable | Slowish (5.0 tok/s) |
| Qwen3-Swallow 32B Japanese · Japanese-enhanced (Institute of Science Tokyo) | BF16 | 69.7GB | Comfortable | Slowish (5.0 tok/s) |
| llm-jp-4 33B thinking Japanese · Japanese-focused (Japan) | BF16 | 70.6GB | Comfortable | Very slow (4.9 tok/s) |
| Qwen3.6 35B-A3B Qwen · Popular fast MoE | BF16 | 74.2GB | Comfortable | Usable (35 tok/s) |
| Llama 3.3 70B Llama · The classic 70B | Q8_0 | 79.8GB | Comfortable | Very slow (4.4 tok/s) |
| Qwen3-Next 80B-A3B Qwen · Large MoE | Q8_0 | 89.0GB | Tight | Fast (64 tok/s) |
| gpt-oss-120b OpenAI · OpenAI open-weight model (MXFP4) | Q4_K_M (MXFP4) | 65.6GB | Comfortable | Fast (74 tok/s) |
| Mistral Small 4 119B Mistral · Large MoE | Q5_K_M | 87.6GB | Tight | Fast (45 tok/s) |
| Qwen3.5 122B-A10B Qwen · Large MoE | Q5_K_M | 91.8GB | Tight | Usable (30 tok/s) |
| Model | Mac M4 Max (128GB) | Ryzen AI Max+ 395 (128GB) | Mac M4 Pro (48GB) | Mac M3 Ultra (256GB) |
|---|---|---|---|---|
| Qwen3 8B | Fast (66 tok/s) | Usable (31 tok/s) | Usable (33 tok/s) | Fast (99 tok/s) |
| Qwen3 14B | Usable (37 tok/s) | Usable (17 tok/s) | Usable (18 tok/s) | Fast (55 tok/s) |
| gpt-oss-20b | Fast (96 tok/s) | Fast (45 tok/s) | Fast (48 tok/s) | Fast (100+ tok/s) |
| Qwen3.6 35B-A3B | Fast (100+ tok/s) | Fast (51 tok/s) | Fast (54 tok/s) | Fast (100+ tok/s) |
| Qwen3 32B | Usable (16 tok/s) | Slowish (7.7 tok/s) | Slowish (8.2 tok/s) | Usable (25 tok/s) |
| Llama 3.3 70B | Slowish (7.7 tok/s) | Very slow (3.6 tok/s) | Won't run | Slowish (11 tok/s) |
With the same VRAM, higher memory bandwidth means faster generation. The Mac M4 Max (128GB) has 546 GB/s.
→ See where the Mac M4 Max (128GB) ranks in our GPU ranking for local LLMs
Estimates for llama.cpp (Ollama, LM Studio) with GGUF files; real numbers can differ by ±10–20%. Data updated 2026-09-27.