MiniMax: MiniMax M2.7

Public pricingIntelligence 76/100Medium memoryDeep thinkingTool use

MiniMax: MiniMax M2.7 is a text model for agent workflows and tool use. It combines reliable tool use and agent behavior with a 197K tokens context window and a low-cost profile. Use it for agent workflows, tool use, and orchestration when quality, speed, and cost matters. It is a practical choice for teams that need reliable output, flexible deployment, and room to scale.

Input

$0.30/1M

Output

$1.20/1M

Cached

$0.06/1M

Batch

$0.20/1M

Calculate your MiniMax M2.7 bill.

Set your workload — see cost at your exact volume.

What would MiniMax M2.7 cost you?

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1,00010,00050,000250,0001M10M

Technical specifications

MiniMax M2.7 at a glance.

Memory

196,608

tokens

Max reply

32,768

tokens

Memory tier

Medium

a long report or a codebase file

Tokenizer

—

Released

Apr 2026

Training cutoff

Jan 2026

Availability

Public pricing

Status

active

Benchmarks

Quality benchmarks

Independent evaluations from public leaderboards. Higher is better.

  • swe_bench_verified

    56.22

What it can do

Capabilities & limits.

  • Understands images
  • Deep step-by-step thinking
  • Uses tools / calls functions
  • Strict JSON output
  • Streams replies
  • Fine-tunable on your data

When to pick MiniMax M2.7

  • Multi-step reasoning, research agents, or hard math.
  • Agentic workflows that call tools or APIs.
  • High-volume workloads where unit cost matters.

When to look elsewhere

  • Your workload involves images — pick a vision-capable model instead.

Alternatives

Similar models to compare.

FAQ

MiniMax M2.7 — the questions we see most.

Pricing, capabilities, alternatives — generated from the same data that powers the calculator above.

Get instant answers from our AI agent

At a typical workload of 50,000 conversations a month with 1,500-token prompts and 800-token replies, MiniMax M2.7 costs roughly $71 per month. Input is $0.30 /1M tokens and output is $1.20 /1M tokens.
MiniMax M2.7 has a 196,608-token context window (medium memory — a long report or a codebase file). That means you can fit about 36,864 words of input and history in a single call.
Beyond text generation, MiniMax M2.7 supports deep step-by-step reasoning, calling functions / tools, strict JSON output, fine-tuning on your own data. It streams replies by default.
MiniMax M2.7 was released in April 2026, with training data cut off around January 2026.
Models in a similar class include MiniMax M2-her, MiniMax M2.1, MiniMax M2. The "Similar models" section below this FAQ links into each.

Still unsure?

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