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Real human-preference Elo from LMArena blind head-to-head votes. Higher is better; — means not yet ranked in that arena. This is measured, not our estimate.
Blended $/1M across tracked versions of this line.
Typical 3:1 output-to-input mix, per 1M tokens
Price as of 2026-05-10 · Source: minimax_official_pricing
Mixed text, image, audio and document workloads that benefit from one model across modalities.
MiniMax M3 is MiniMax's frontier multimodal coding and agent model with a 1M-token context window.
minimax-m3 is a Multimodal model from MiniMax (CN). HotON.ai tracks it at $0.30 per 1M input tokens and $1.20 per 1M output tokens, with a 1000K-token context window. Its composite efficiency score is 96/100 at an estimated $0.001 per successful task.
minimax-m3 is tracked at $0.30 per 1M input tokens and $1.20 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $0.97 per 1M tokens. Figures are illustrative demo data.
Mixed text, image, audio and document workloads that benefit from one model across modalities.
minimax-m3 supports up to a 1000K-token context window — large enough for long documents and extended conversations in a single request.
Within the HotON.ai tracked set, minimax-m3 is cheaper than 51% of models on input price and ranks #10 of 535 by overall efficiency.
Yes — gemini-2.0-flash-001 is a lower-cost option at $0.40 per 1M output tokens, while still covering similar Multimodal use cases. Compare them side by side on HotON.ai.
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HotON.ai — minimax-m3 (MiniMax): $0.30/1M input, $1.20/1M output, as of 2026-05-10. https://hoton.ai/en/models/minimax-minimax-m3Pricing is real (via the TestKey catalog, updated daily). Quality (Arena Elo) is real where the model is ranked on LMArena. Efficiency is a modeled composite of real price and context.