llamaperf

M4 Pro 64GB vs NVIDIA RTX 5090 Laptop 24GB for local LLMs

33 reports on the M4 Pro 64GB and 6 on the NVIDIA RTX 5090 Laptop 24GB

Which is faster for local LLMs?

On Qwen3.8 27B at 4-bit, the M4 Pro 64GB has 12.9 generation tokens/s (4 runs); prompt processing 126.2 tokens/s (4 runs); the NVIDIA RTX 5090 Laptop 24GB has 33.5 generation 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 3.3x higher on the NVIDIA RTX 5090 Laptop 24GB (273 GB/s on the M4 Pro 64GB, 896 on the NVIDIA RTX 5090 Laptop 24GB).

M4 Pro 64GB
Memory
64GB unified
Memory bandwidth
273 GB/s
FP16 compute
9.2 TFLOPS
Reports
33
NVIDIA RTX 5090 Laptop 24GB
Memory
24GB
Memory bandwidth
896 GB/s
FP16 compute
200 TFLOPS
Reports
6

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

ModelM4 Pro 64GBNVIDIA RTX 5090 Laptop 24GB
Qwen3.8 27B4-bit12.94 runsPP 126.2 (4 runs)llama.cpp, 2 not statedcontext not stated33.52 runsllama.cpp, 1 not stated64K to 100K context

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.

ModelM4 Pro 64GBNVIDIA RTX 5090 Laptop 24GB
Qwen3.8 27B7.7 t/sQ8_032.4 t/sQ4_K_M
Qwen3.8 125B · 6B active34.9 t/sQ2_K19.4 t/sQ2_K, experts in RAM
Qwen3.6 35B · 3B active24.1 t/sQ8_0115.0 t/sQ4_K_S
DeepSeek V4 Flash 284B · 13B activedoesn't fit at these settingsdoesn't fit at these settings
Qwen3.6 27B7.7 t/sQ8_032.4 t/sQ4_K_M
Gemma 4 26B · 4B active20.7 t/sQ8_073.2 t/sQ5_K_S
DeepSeek V4.1 Flash 552B · 16B activedoesn't fit at these settingsdoesn't fit at these settings

Change the context, RAM or model in the calculator: M4 Pro 64GB · NVIDIA RTX 5090 Laptop 24GB

Every report on each card, with its source: M4 Pro 64GB · NVIDIA RTX 5090 Laptop 24GB

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