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Model details

MiniMax-M2.5-highspeed

MiniMax-M2.5-highspeed is part of the MiniMax M-series of language models and shares the same underlying identity as the base MiniMax-M2.5 release, including the self-hosted repository identifier MiniMaxAI/MiniMax-M2.5. It is documented as an open-weight model aimed at coding, agentic tool use, search, and office productivity workflows, positioning it as a general-purpose assistant for software engineering and knowledge work rather than a narrow single-task system. Within the MiniMax API model catalog it sits alongside MiniMax-M2.5 in the legacy section, indicating that newer M-series offerings such as M3 and M2.7 are the recommended path for new integrations while the M2.5 line remains accessible for existing deployments.

The defining characteristic of the -highspeed variant is its emphasis on significantly faster inference compared to the standard M2.5, while preserving the same underlying capabilities, making it well suited to latency-sensitive coding assistants and interactive developer tooling. Its feature profile highlights polyglot code mastery, precision code refactoring, and low-latency response, reflecting MiniMax's focus on the M-series as workhorses for real-world engineering tasks. For practitioners choosing a model, MiniMax-M2.5-highspeed fits scenarios where responsiveness matters as much as raw output quality, particularly when refactoring or generating code across multiple languages, while teams building greenfield integrations should weigh it against the more recent M2.7 and M3 generations that now anchor MiniMax's current catalog.

DevPass (LLM Gateway)minimax-m2.5-highspeedminimax

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Provider
DevPass (LLM Gateway)
Model key
minimax-m2.5-highspeed
Release date
Feb 13, 2026
Last updated
Feb 13, 2026
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$0.60
Output token cost
$2.40

Limits

Output tokens
131,072 tokens
Context window
204,800 tokens

Transparent token rates

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Rates are shown per one million tokens. Combined means one million input plus one million output tokens.

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