M5 Max 128GB mlx_lm: gpt-oss-120b-MXFP4-Q8 prefill at 32k (32836 prompt tokens)
2537.42 tok/s (single-request prefill, 32836 prompt tokens)
Fields
id
benchmarks/m5max128-mlx-gptoss-120b-mxfp4-q8-32k-ppMetric
prefill_tok_s
Value
2,537.42
Unit
tok/s (single-request prefill, 32836 prompt tokens)
Model
gpt-oss-120b-MXFP4-Q8
Methodology
mlx_lm.generate on one 14-inch MacBook Pro, M5 Max, 128 GB unified memory, 40-core GPU (u/cryingneko). Command: mlx_lm.generate --model <local path> --prompt "$(cat /tmp/prompt_<N>.txt)" --max-tokens 128. ONE request, batch size 1: the prompt-tokens-per-sec line is prefill of that single prompt and the generation-tokens-per-sec line is decode of that single completion. NOT aggregate. mlx-lm version not printed. Author states these replaced an earlier BatchGenerator run. Model path /Volumes/SSD/Models/gpt-oss-120b-MXFP4-Q8. Prompt: 32836 tokens. Generation: 128 tokens. Peak memory: 65.461 GB. PREFILL of one request, not aggregate.
Measured by
third_party
Reproducible
yes
notes
Prompt tokens-per-sec line of the mlx_lm.generate stdout. 4k rows for this model were already filed from the siliconscore CSV (ss-m5max-128-*); this is the 32k context the CSV pass did not keep.
Notes
Prompt tokens-per-sec line of the mlx_lm.generate stdout. 4k rows for this model were already filed from the siliconscore CSV (ss-m5max-128-*); this is the 32k context the CSV pass did not keep.