llamaperf

M6 32GB vs NVIDIA RTX 3090 for local LLMs

2 reports on the M6 32GB and 165 on the NVIDIA RTX 3090

Which is faster for local LLMs?

On Qwen3.6 35B · 3B active at 4-bit, the M6 32GB runs at 63.8 tokens per second (one run) and the NVIDIA RTX 3090 at 101.7 (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 5.5x higher on the NVIDIA RTX 3090 (171 GB/s on the M6 32GB, 936 on the NVIDIA RTX 3090).

M6 32GB
Memory
32GB unified
Memory bandwidth
171 GB/s
FP16 compute
not on record
Reports
2
NVIDIA RTX 3090
Memory
24GB
Memory bandwidth
936 GB/s
FP16 compute
142 TFLOPS
Reports
165

Measured on both

Median tokens per second 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 quant level. Engines and context lengths can still differ between the runs. How to read these

ModelM6 32GBNVIDIA RTX 3090
Qwen3.6 35B · 3B active4-bit63.8one run101.7one run

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.

ModelM6 32GBNVIDIA RTX 3090
Qwen3.6 35B · 3B active38.2 t/sQ3_K_M120.1 t/sQ4_K_S
Qwen3.8 27B10.5 t/sQ4_K_S33.9 t/sQ4_K_M
Qwen3.8 125B · 6B activedoesn't fit at these settings19.4 t/sQ2_K, experts in RAM
DeepSeek V4 Flash 284B · 13B activedoesn't fit at these settingsdoesn't fit at these settings
Qwen3.6 27B10.5 t/sQ4_K_S33.9 t/sQ4_K_M
Gemma 4 26B · 4B active23.2 t/sQ4_K_M76.4 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: M6 32GB · NVIDIA RTX 3090

Every report on each card, with its source: M6 32GB · NVIDIA RTX 3090

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