MiniMax: MiniMax M1
Analysis Summary
MiniMax M1 is a long-context reasoning model with a one-million-token window, tool use, and function calling. Its mathematical performance and LiveCodeBench result make it more capable for technical work than its general intelligence index suggests, while the text-only interface keeps deployment straightforward.
The model fits codebase exploration, document-heavy analysis, structured automation, and agent workflows that benefit from retaining large amounts of context. Function calling supports practical orchestration, but the low TerminalBench Hard result indicates that autonomous shell-based work needs supervision. Instruction following and long-context reliability are usable rather than exceptional for client-facing editorial production.
Pricing is moderate, with low input cost and a higher output rate. Adopt it for large-context technical workflows where context capacity and tool access matter more than polished general writing.
Assessed September 7, 2026
Editorial notes
MiniMax M1 combines a million-token context with tool use, function calling, and strong mathematical and coding results. It suits long-context automation and engineering tasks, though terminal reliability and general reasoning are less consistent than leading models.
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DFO Verdict
MiniMax M1 combines a million-token context with tool use, function calling, and strong mathematical and coding results. It suits long-context automation and engineering tasks, though terminal reliability and general reasoning are less consistent than leading models.
Benchmark scores
Magenta = intelligence · Ink = technical/agentic · Cyan = content & long-context · Grey = community benchmarks. Data: Artificial Analysis, Hugging Face.
17.7 Intelligence Index·18.6 Agentic Index·61 Math Index
How MiniMax: MiniMax M1 compares
MiniMax: MiniMax M1 ranks #149 of 438 AI models we track for overall intelligence, #93 of 192 for agentic tasks. Its 1M-token context window is larger than 83% of the models we list. At $0.40 per million input tokens it is cheaper than 42% of comparable models.
Dark bar = input · light bar = output, scaled to the priciest peer.
1M tokens ≈ 8 full-length novels or ~2,500 pages of business documents in a single request.
Strongest on value. The pulled-in technical corner is the trade-off, and if the shape matters more than the price, this is your model.
Compare shapes side-by-side →Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $0.40 | $0.000400 |
| Output | $2.20 | $0.002200 |
What would MiniMax: MiniMax M1 cost your business?
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A website chatbot handling around 100 customer conversations a day, a few short messages each.
Full calculator with 776 models → Price Calculator
These numbers get smaller with the right architecture.
We route routine calls to cheap models and save MiniMax: MiniMax M1 for the hard ones. Most clients cut their estimate by 60-80%.
Talk to our teamAbout 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..
Frequently asked questions about MiniMax: MiniMax M1
How much does MiniMax: MiniMax M1 cost?
MiniMax: MiniMax M1 costs $0.40 per million input tokens and $2.20 per million output tokens.
What is the context window of MiniMax: MiniMax M1?
MiniMax: MiniMax M1 has a context window of 1,000,000 tokens (1M).
What can MiniMax: MiniMax M1 do?
MiniMax: MiniMax M1 supports tool use and function calling.
Who created MiniMax: MiniMax M1?
MiniMax: MiniMax M1 is developed by MiniMax and was released on June 17, 2025.