MiniMax Agent
Shanghai-based MiniMax bundles a foundation-model line (ABAB → MiniMax-01 → M1 → M2.x) with a consumer MiniMax Agent that evaluates tasks, assembles an 'Agent Team' for them, and learns user-specific habits into custom skills.
Description
MiniMax was founded in 2021 by SenseTime alumni and listed in Hong Kong in January 2026. It develops a series of multimodal foundation models with strong code and Agent capabilities; the company markets MiniMax-M1 as the world's first open-source, large-scale, hybrid-attention reasoning model with an 80K-token reasoning output and tool-use benchmark leadership among open-weights. MiniMax Agent is the consumer surface: an assistant that evaluates a task, builds an agent team, learns user habits, and turns repetitive workflows into custom skills. The API exposes function calling for tool use; verifiable English platform docs were patchy at access time (several pages 404 or redirect repeatedly between intl.minimaxi.com / platform.minimax.io).
Solution
Two surfaces. (1) MiniMax Agent product: hosted loop that evaluates the user task, assembles an Agent Team, and dispatches sub-tasks; surfaces skills, memory and schedules in a single chat. (2) MiniMax API (M1 / M2.x via Chat Completions): standard tool-call loop; reasoning models expose a long 80K-token thinking budget and benchmark in TAU-bench style agentic tool-use scenarios.
Primary use cases
- consumer multi-skill assistant (work and life tasks)
- agent-team task decomposition over arbitrary user goals
- open-weight reasoning model for self-hosted tool-use agents
- long-output reasoning (80K token thinking budget)
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