Minimax M2.5
Minimax M 2.5 is a chat model developed by Minimax, exceling in code generation and reasoning tasks, particularly in coding, agentic tool use, and search. With a context window of 196,608 tokens, this open-source model demonstrates notable technical capability.
Input
Output
Context
205K
Max Output
8K
Parameters
228.7B
Technical Specifications
Input Modalities
Output Modalities
Capabilities
Loading capabilities…
Benchmarks
Estimated GPU requirements for Minimax M2.5
Estimates based on INT8 quantization at up to 32K context. A count above one assumes tensor parallelism across the cards. Actual requirements vary by framework and configuration.
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Frequently asked questions about Minimax M2.5
Answered from the entry's own fields: context, license, modalities, evidence, serving and the memory to self-host.
Minimax M2.5 advertises a context window of 204,800 tokens, with a maximum output of 8,192 tokens in a single response. The figure is the creator's published maximum; a given host may serve less, and the gateway routes on what each host actually serves.
Yes. Minimax M2.5 is an open-weight model released under the Other license, so the weights can be downloaded and self-hosted within that license's terms.
Minimax M2.5 accepts Text and produces Text. The capabilities card on this page lists which API features each deployment honours, such as function calling and structured output, with the source each was checked against.
Minimax M2.5 has published results from Artificial Analysis, shown by suite in the benchmarks card above exactly as the publisher reported them. Scores are not combined across suites, and a suite that has not measured Minimax M2.5 is shown as not available rather than estimated.
Not on the managed pool today; Minimax M2.5 is listed for reference and comparison. Connect your own provider key or endpoint that serves it and the gateway runs it on your account, with routing decisions recorded the same way.
About 221.0 GB at INT8 for the weights and a default context, from the catalog's 228.7B parameter count; FP16 needs roughly twice that, and long contexts or many concurrent requests add KV cache on top. The GPU section on this page lists cards that hold it, and the capacity planner sizes it for your context length and traffic.
Fields collected from public registries, host APIs and benchmark publishers, each tagged with its source.
Last updated: Sep 13, 2026
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