llamaperf

M2 Max 64GB vs M4 Max 128GB for local LLMs

20 reports on the M2 Max 64GB and 52 on the M4 Max 128GB

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 Max 128GB has 81.1 generation tokens/s (one run); prompt processing 1423.5 tokens/s (one run). 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 33% higher on the M4 Max 128GB (410 GB/s on the M2 Max 64GB, 546 on the M4 Max 128GB). Across 5 shared models with generation measurements on both cards, the M2 Max 64GB's median is higher on 0 and the M4 Max 128GB's on 5.

M2 Max 64GB
Memory
64GB unified
Memory bandwidth
410 GB/s
FP16 compute
13.6 TFLOPS
Reports
20
M4 Max 128GB
Memory
128GB unified
Memory bandwidth
546 GB/s
FP16 compute
18.4 TFLOPS
Reports
52

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

ModelM2 Max 64GBM4 Max 128GB
Qwen3.6 35B · 3B active4-bit77.52 runsLM Studio, Ollama32K to 256K context81.1one runPP 1423.5 (one run)llama.cppcontext not stated
Gemma 4 26B · 4B active4-bit61.6one runPP 465.2 (one run)MLXcontext not stated88.1one runPP 1408.1 (one run)llama.cppcontext not stated
gpt-oss 21B · 3.6B active4-bit85.5one runPP 501.5 (one run)MLXcontext not stated123.1one runPP 1577.0 (one run)llama.cppcontext not stated
Qwen3.5 9B4-bit62.7one runPP 321.2 (one run)MLXcontext not stated68.0one runPP 832.1 (one run)llama.cppcontext not stated
Qwen3.5 4B4-bit70.4one runTransformerscontext not stated101.4one runPP 1476.8 (one run)llama.cppcontext 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.

ModelM2 Max 64GBM4 Max 128GB
Qwen3.6 35B · 3B active32.9 t/sQ8_021.2 t/sFP16
Gemma 4 26B · 4B active28.2 t/sQ8_018.2 t/sFP16
gpt-oss 21B · 3.6B active62.7 t/sQ8_040.5 t/sFP16
Qwen3.5 9B15.7 t/sFP1620.2 t/sFP16
Qwen3.5 4B35.2 t/sFP1645.5 t/sFP16
Qwen3.8 27B10.4 t/sQ8_06.7 t/sFP16
Qwen3.8 125B · 6B active47.5 t/sQ2_K30.7 t/sQ5_K_S
DeepSeek V4 Flash 284B · 13B activedoesn't fit at these settings48.3 t/sQ2_K
Qwen3.6 27B10.4 t/sQ8_06.7 t/sFP16
DeepSeek V4.1 Flash 552B · 16B activedoesn't fit at these settingsdoesn't fit at these settings
GLM-5.3 320B · 18B activedoesn't fit at these settingsdoesn't fit at these settings

Change the context, RAM or model in the calculator: M2 Max 64GB · M4 Max 128GB

Every report on each card, with its source: M2 Max 64GB · M4 Max 128GB

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