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MiniMax
minimax/minimax-m1Catalogue: Indexed in the reference catalogue; nothing on this deployment answers as this model yet.
Published by the vendor; the platform bills at the target's declared price.
MiniMax minimax/minimax-m1
MiniMax-M1 is a large-scale, open-weight reasoning model designed for extended context and high-efficiency inference. It leverages a hybrid Mixture-of-Experts (MoE) architecture paired with a custom "lightning attention" mechanism, allowing it...
MiniMax M1 earns a request when it needs step-by-step reasoning, tool calls, very long inputs; a short, general request would go to Nemotron 3.5 Super VL (free) instead - free per million input tokens against $0.55 here; and the hardest requests, where the quality floor rules it out, to Claude Opus 5.5 (batch). Your rules decide the floor; the trace shows the comparison for every request.
Lower input price and an intelligence index within 5 points.
A higher intelligence index, best first, with the price it comes at.
Nothing on this deployment answers as this model yet. Connect your own provider under Model providers, or add a target to your catalogue - the router picks it up without retraining.
# targets.yaml - declare a target that runs MiniMax M1
targets:
- id: minimax-m1
kind: llm
name: MiniMax M1
metadata:
model: minimax/minimax-m1 # links the target to this catalogue entry
capabilities:
domains: [general]
supports_tools: true
context_window: 1000000
cost:
usd_per_1k_tokens: 0.001375Input list price per million tokens; MiniMax M1 is the most expensive of 9 listed.
Other models by the same vendor in the catalogue.
Photo: RDNE Stock project