M5 Max LLM benchmark
No M5 Max LLM benchmarks yet. Be the first to submit a signed, reproducible tok/s run from your own M5 Max.
Will it run local LLMs?
No signed M5 Max run yet, but its 128GB of unified memory tells you what fits. At 4-bit it comfortably runs models up to about 115B parameters with room for context, and up to roughly 181B with tighter quantization. Check a specific model with the VRAM-fit tool.
For measured decode speed on the nearest hardware we have benchmarked: M3 Ultra · M4 Max · M3 Pro. Run the suite on your M5 Max to fill this page in.
No M5 Max benchmarks yet.
Run on YOUR hardware to populate this page: pipx install llm-speed && llm-speed bench
$ pipx install llm-speed && llm-speed bench
Community folklore on M5 Max
94 unverified claims extracted from Reddit/HN comments. Lower trust than signed runs above; every row links to the source.
- communityconfidence 70%
24.79tok/s — Gemma 3 27B on M5 Max via lm-studio
our signed data: M5 Max · Gemma 3 27B
“W|**+45W** (Thermal throttling risk)| |**Time to First Token (Prefill)**|89.83s|24.35s|**\~3.7x Faster**| |**Generation Speed**|23.16 tok/s|24.79 tok/s|**+1.63 tok/s** (Marginal)| |**Total Time**|847.87s|787.85s|**\~1 minute faster** overall| |**Prompt Tokens**|19,761|19,761|Same…”
- communityconfidence 70%
23.16tok/s — Gemma 3 27B on M5 Max via lm-studio
our signed data: M5 Max · Gemma 3 27B
“|< 70W|< 115W|**+45W** (Thermal throttling risk)| |**Time to First Token (Prefill)**|89.83s|24.35s|**\~3.7x Faster**| |**Generation Speed**|23.16 tok/s|24.79 tok/s|**+1.63 tok/s** (Marginal)| |**Total Time**|847.87s|787.85s|**\~1 minute faster** overall| |**Prompt Tokens**|19,761…”
- communityconfidence 70%
24.79tok/s — Gemma 3 27B on M5 Max via lm-studio
our signed data: M5 Max · Gemma 3 27B
“W|**+45W** (Thermal throttling risk)| |**Time to First Token (Prefill)**|89.83s|24.35s|**\~3.7x Faster**| |**Generation Speed**|23.16 tok/s|24.79 tok/s|**+1.63 tok/s** (Marginal)| |**Total Time**|847.87s|787.85s|**\~1 minute faster** overall| |**Prompt Tokens**|19,761|19,761|Same…”
- communityconfidence 70%
23.16tok/s — Gemma 3 27B on M5 Max via lm-studio
our signed data: M5 Max · Gemma 3 27B
“|< 70W|< 115W|**+45W** (Thermal throttling risk)| |**Time to First Token (Prefill)**|89.83s|24.35s|**\~3.7x Faster**| |**Generation Speed**|23.16 tok/s|24.79 tok/s|**+1.63 tok/s** (Marginal)| |**Total Time**|847.87s|787.85s|**\~1 minute faster** overall| |**Prompt Tokens**|19,761…”
- communityconfidence 60%
31.60tok/s — Qwen 2.5 72B on M5 Max via mlx
our signed data: M5 Max · Qwen 2.5 72B
“oretical maximum bandwidth utilization. # 2. MLX is Dramatically Faster for Qwen 3.5 * **llama.cpp**: 16.5 tok/s (Q6\_K, 21GB) * **MLX**: 31.6 tok/s (4bit, 16GB) * **Delta**: MLX is **92% faster** (1.9x speedup) This confirms the community reports that llama.cpp has a known pe…”
- communityconfidence 60%
16.50tok/s — Qwen 2.5 72B on M5 Max via llama.cpp
our signed data: M5 Max · Qwen 2.5 72B
“onsistently achieves \~73-75% of theoretical maximum bandwidth utilization. # 2. MLX is Dramatically Faster for Qwen 3.5 * **llama.cpp**: 16.5 tok/s (Q6\_K, 21GB) * **MLX**: 31.6 tok/s (4bit, 16GB) * **Delta**: MLX is **92% faster** (1.9x speedup) This confirms the community r…”
- communityconfidence 60%
31.60tok/s — Qwen 2.5 72B on M5 Max via mlx
our signed data: M5 Max · Qwen 2.5 72B
“oretical maximum bandwidth utilization. # 2. MLX is Dramatically Faster for Qwen 3.5 * **llama.cpp**: 16.5 tok/s (Q6\_K, 21GB) * **MLX**: 31.6 tok/s (4bit, 16GB) * **Delta**: MLX is **92% faster** (1.9x speedup) This confirms the community reports that llama.cpp has a known pe…”
- communityconfidence 60%
16.50tok/s — Qwen 2.5 72B on M5 Max via llama.cpp
our signed data: M5 Max · Qwen 2.5 72B
“onsistently achieves \~73-75% of theoretical maximum bandwidth utilization. # 2. MLX is Dramatically Faster for Qwen 3.5 * **llama.cpp**: 16.5 tok/s (Q6\_K, 21GB) * **MLX**: 31.6 tok/s (4bit, 16GB) * **Delta**: MLX is **92% faster** (1.9x speedup) This confirms the community r…”
- communityconfidence 60%
31.60tok/s — Qwen 2.5 72B on M5 Max via mlx
our signed data: M5 Max · Qwen 2.5 72B
“oretical maximum bandwidth utilization. # 2. MLX is Dramatically Faster for Qwen 3.5 * **llama.cpp**: 16.5 tok/s (Q6\_K, 21GB) * **MLX**: 31.6 tok/s (4bit, 16GB) * **Delta**: MLX is **92% faster** (1.9x speedup) This confirms the community reports that llama.cpp has a known pe…”
- communityconfidence 60%
16.50tok/s — Qwen 2.5 72B on M5 Max via llama.cpp
our signed data: M5 Max · Qwen 2.5 72B
“onsistently achieves \~73-75% of theoretical maximum bandwidth utilization. # 2. MLX is Dramatically Faster for Qwen 3.5 * **llama.cpp**: 16.5 tok/s (Q6\_K, 21GB) * **MLX**: 31.6 tok/s (4bit, 16GB) * **Delta**: MLX is **92% faster** (1.9x speedup) This confirms the community r…”
Common questions about M5 Max
Direct Q&A drawn from the runs above: fastest LLM, supported model classes, backend rankings, quantization guidance.