M2 Max 64GB vs M4 Pro 64GB for local LLMs
20 reports on the M2 Max 64GB and 33 on the M4 Pro 64GB
Which is faster for local LLMs?
On Qwen3.6 35B · 3B active at 4-bit, the M2 Max 64GB has 77.5 generation tokens/s (2 runs); the M4 Pro 64GB has 57.5 generation tokens/s (2 runs); prompt processing 767.1 tokens/s (2 runs). Those are community reports whose engines and settings differ, so the gap is a rough sign, not a controlled measure of the two cards. Memory bandwidth, which caps how fast a card can write, is 50% higher on the M2 Max 64GB (410 GB/s on the M2 Max 64GB, 273 on the M4 Pro 64GB). Across 3 shared models with generation measurements on both cards, the M2 Max 64GB's median is higher on 3 and the M4 Pro 64GB's on 0.
- Memory
- 64GB unified
- Memory bandwidth
- 410 GB/s
- FP16 compute
- 13.6 TFLOPS
- Reports
- 20
- Memory
- 64GB unified
- Memory bandwidth
- 273 GB/s
- FP16 compute
- 9.2 TFLOPS
- Reports
- 33
Measured on both
Generation and prompt processing speeds from plain runs (one device, one request, no speculative decoding, the whole model in the device's memory) of the same model size at the same bit class. Each side shows the engines and reported context behind its median. Context can mean a configured window or prompt depth, so these are community comparisons with differing settings. How to read these
| Model | M2 Max 64GB | M4 Pro 64GB |
|---|---|---|
| Qwen3.6 35B · 3B active4-bit | 77.52 runsLM Studio, Ollama32K to 256K context | 57.52 runsPP 767.1 (2 runs)llama.cpp, 1 not statedcontext not stated |
| gpt-oss 21B · 3.6B active4-bit | 85.5one runPP 501.5 (one run)MLXcontext not stated | 73.63 runsPP 834.2 (3 runs)llama.cpp, 2 not statedcontext not stated |
| Gemma 4 26B · 4B active4-bit | 61.6one runPP 465.2 (one run)MLXcontext not stated | 57.32 runsPP 774.8 (2 runs)llama.cpp, 1 not statedcontext not stated |
Estimated by the calculator
The quant the calculator recommends for each card and its estimated speed at a 32,768-token context with 32 GB of system RAM, from memory bandwidth and the model's shape. Where a model was also measured above, the measurement wins.
| Model | M2 Max 64GB | M4 Pro 64GB |
|---|---|---|
| Qwen3.6 35B · 3B active | 32.9 t/sQ8_0 | 24.1 t/sQ8_0 |
| gpt-oss 21B · 3.6B active | 62.7 t/sQ8_0 | 46.0 t/sQ8_0 |
| Gemma 4 26B · 4B active | 28.2 t/sQ8_0 | 20.7 t/sQ8_0 |
| Qwen3.8 27B | 10.4 t/sQ8_0 | 7.7 t/sQ8_0 |
| Qwen3.8 125B · 6B active | 47.5 t/sQ2_K | 34.9 t/sQ2_K |
| DeepSeek V4 Flash 284B · 13B active | doesn't fit at these settings | doesn't fit at these settings |
| Qwen3.6 27B | 10.4 t/sQ8_0 | 7.7 t/sQ8_0 |
| DeepSeek V4.1 Flash 552B · 16B active | doesn't fit at these settings | doesn't fit at these settings |
| GLM-5.3 320B · 18B active | doesn't fit at these settings | doesn't fit at these settings |
Change the context, RAM or model in the calculator: M2 Max 64GB · M4 Pro 64GB
Every report on each card, with its source: M2 Max 64GB · M4 Pro 64GB