llamaperf

Minimax M3

MiniMax · 3 reports

Minimax M3 VRAM requirements by size and quant →

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Reported performance for Minimax M3

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NVIDIA hardware
generation:
113.0 tokens/s
prompt processing (prefill):
2800.0 tokens/s
quant:
MXFP4 (MXFP4)
kv:
BF16

Reported by the source; GPU count, offloading and concurrent requests can change these figures. Prompt-processing speed is input throughput, not time to first token. Check the full setup before comparing.

long-contexttool-usevision

User reports MiniMax-M3 at ~113 tok/s single-stream decode on 4x RTX PRO 6000 Blackwell (96 GB each). Setup is vLLM with the MXFP4 checkpoint (~256 GB, ~60 GB per card), BF16 KV cache, tensor parallelism 4, and 250K context; cold prefill runs ~2,800 tok/s flat from 8K to 131K. Four concurrent requests reach ~184 tok/s aggregate. A second NVFP4/SGLang configuration on the same host decodes at ~87 tok/s single-stream with a ~643K-token KV pool and image/video support.

Oct 9, 2026
NVIDIA hardware
generation:
88.5 tokens/s
quant:
NVFP4 (safetensors)
kv:
BF16

Reported by the source; GPU count, offloading and concurrent requests can change these figures. Prompt-processing speed is shown only when the source reports it; generation speed cannot tell us time to first token. Check the full setup before comparing.

tool-usevisionlong-contextagentic

User reports MiniMax-M3-uncensored-NVFP4 at about 88.5 tokens/s for a warmed-up single-request decode on 4x NVIDIA RTX PRO 6000 Blackwell 96 GB. Setup is SGLang with ModelOpt NVFP4 routed-expert weights, BF16 KV cache, tensor parallel size 4, 32,768-token configured context, CUDA graph enabled, and two concurrent requests allowed. The figure is a measured short-request decode rate after warmup; the checkpoint was compressed from 854.2 GB BF16 to 260.4 GB. Long-context probe recalled a sentinel from a 20,212-token prompt, and vLLM was not accepted for this deployment.

Oct 9, 2026
Tone: negativeApple hardware
generation:
17.3 tokens/s
quant:
4bit (MLX)

Reported by the source; GPU count, offloading and concurrent requests can change these figures. Prompt-processing speed is shown only when the source reports it; generation speed cannot tell us time to first token. Check the full setup before comparing.

User reports a bug in oMLX 0.6.4 distributed clustering where the coordinator fails to release RAM and GPU after a crash. The model is mlx-community/MiniMax-M3-4bit at 236 GB, run across rank 0 on a Mac Studio M3 Ultra 256GB and rank 1 on a Mac Studio M2 Ultra 192GB. The first completion produced 17 tokens from a 7,693-token prompt at 17.3 tok/s. The crash was triggered by overlapping requests with pipeline_prefill_overlap and coalesced batching. After the crash, roughly 116 GB of wired memory has no owning process and the GPU stays pinned at 100%, requiring a reboot. The M2 Ultra worker released memory cleanly. The user also reports that MiniMax-M3 crashes the cluster after the first prompt.

Sep 10, 2026
Engines people run Minimax M3 with
EngineReports
SGLang1
oMLX1
vLLM1

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Reported configurations

Individual observations from this page, not expected speeds or a ranking. Select a model to open its report, with the source and offloading conditions. Reported context may be a limit rather than actual input length.

Model / hardwareQuant / engineReported contextGeneration
Minimax M3 428B (23B active)
4× NVIDIA RTX Pro 6000 Blackwell
MXFP4
vLLM
250,000113.0 tokens/s
Minimax M3 428B (23B active) uncensored
4× NVIDIA RTX Pro 6000 Blackwell
NVFP4
SGLang
32,76888.5 tokens/s
Minimax M3 428B (23B active)
2× M3 Ultra 256GB
4bit
oMLX
Not reported17.3 tokens/s