MiniMax: MiniMax M2.7

minimax/minimax-m2.7

MiniMax-M2.7 is a next-generation large language model designed for autonomous, real-world productivity and continuous improvement. Built to actively participate in its own evolution, M2.7 integrates advanced agentic capabilities through multi-agent...

Modalities

In / out price

$0.21 / $0.84 per 1M

Context

205K

Released

Mar 18, 2026

Why use MiniMax M2.7

Step-by-step reasoning mode
Tool and function calling (agent-ready)
Structured (JSON) outputs

Pricing

Input	$0.21 / 1M tokens
Output	$0.84 / 1M tokens
Cached input (read)	$0.042 / 1M tokens

List prices via OpenRouter, checked daily. Real cost depends on the provider and on reasoning tokens.

How it ranks

Intelligence index22.8

Coding index52.6

Agentic index15.3

Source: Artificial Analysis (artificialanalysis.ai) via OpenRouter (openrouter.ai/rankings).

Cost calculator

Pick a task, set how often you run it, and compare what it costs on each model.

TaskInput tokens≈ 602 wordsOutput tokens≈ 1,504 wordsRuns per month

Input served from cache: 0%Repeated prompts (same instructions or document) are billed at the cheaper cache-read price where the model supports it.

Model	Per run	Per month	Per 1,000 runs
MiniMax: MiniMax M2.7	$0.0018	$1.85	$1.85

Estimates from list prices via OpenRouter; real bills vary by provider and reasoning tokens.

Will it fit? Context window simulator

Each square is about one page (500 words). Colored squares are your content; grey squares are free space in the model's context window.

Your content

Novel (90,000 words)

Total: about 120,000 tokens (≈ 90,226 words). Token counts are estimates.

Models

Zoom (square size): 6pxZoom out to see a whole million-token window at once.