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MiniMax: MiniMax M2

minimax/minimax-m2

MiniMaxopen-weight205K context4 providersIntelligence 80.5

Cheapest provider

$0.26 / 1M

AtlasCloud

Fastest provider (p95)

187 tok/s

Google

Intelligence (composite)

80.5

MMLU-Pro · HumanEval · math · GPQA

Per-provider performance

Latency / throughput / uptime / price measured across providers over the last 30 minutes of live traffic. This is what proves “sourced cheapest” — Atlas mode draws on these per call to serve the cheapest path that holds quality.

ProviderQuantInput $/1MOutput $/1MLatency p50 / p95Throughput p50 / p95Uptime 30mSuccess
AtlasCloudq8· fp8$0.2550$1.00001739ms / 8382ms7 / 48.8 tok/s95.5%
Minimaxq8· fp8$0.2550$1.02001312ms / 4120ms10 / 77.5 tok/s100.0%
Googleundisclosed$0.3000$1.20003044ms / 4399ms158 / 187 tok/s100.0%
Novitaq8· fp8$0.3000$1.20001465ms / 8372ms75 / 97 tok/s100.0%

“—” means live telemetry hasn’t accumulated enough recent traffic for that endpoint. “undisclosed” means the provider serves the model but doesn’t expose the quantization label (typically running fp8 / int8 internally).

Intelligence breakdown

Composite score is a weighted average of public benchmarks (30% MMLU-Pro, 25% code pass@1, 25% math, 20% GPQA). Numbers come from model cards and the Artificial Analysis intelligence harness; missing components are renormalised over what’s present.

MMLU-Pro

82.0

broad reasoning

Code

83.0

pass@1 (HumanEval / LiveCodeBench)

AIME 2025

78.0

math accuracy

GPQA Diamond

78.0

hard reasoning

Source: Artificial Analysis (AA-aligned) — MiniMax-M2 (MMLU-Pro 82, GPQA-D 78, LiveCodeBench 83, AIME25 78); github.com/MiniMax-AI/MiniMax-M2

How Atlas mode sources MiniMax: MiniMax M2

  • Strict mode — pin MiniMax: MiniMax M2 exactly and we pass it straight through, sourced from the cheapest provider above. The same model, no substitutions — currently AtlasCloud at $0.26/1M.
  • Atlas mode — the default. Each call is auto-optimized for the cheapest path that holds quality, at least 5% off going direct from call one and climbing as it ramps. You always see which model served the call and exactly what you saved — thumbs-down anything you don’t like for a full refund.