MiniMax: MiniMax M2.7

Public pricingIntelligence 76/100Medium memory심층 추론도구 활용

MiniMax: MiniMax M2.7은 에이전트 워크플로와 도구 활용에 맞춘 텍스트 모델입니다. 안정적인 도구 사용과 에이전트 동작, 197K tokens의 컨텍스트, 저비용 특성을 결합해 agent workflows, tool use, and orchestration에서 안정적인 작업을 돕습니다. 특히 품질, 속도, 비용가 중요한 경우에 잘 맞으며, 안정적인 출력, 유연한 배포, 확장성을 중시하는 팀에 실용적입니다. 안정적인 응답, 넓은 문맥 처리, 그리고 시제품부터 운영까지 이어지는 유연성이 필요할 때 유용합니다. 안정적인 응답, 넓은 문맥 처리, 그리고 시제품부터 운영까지 이어지는 유연성이 필요할 때 유용합니다.

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?

Adjust the workload to see your monthly bill.

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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