MiniMax: MiniMax M2.7

Public pricingIntelligence 76/100Medium memoryगहरी सोचटूल उपयोग

MiniMax: MiniMax M2.7 एक टेक्स्ट मॉडल है, जिसे agent workflows और tool use के लिए बनाया गया है। यह विश्वसनीय tool use और agent behavior, 197K tokens का context और कम लागत profile जोड़कर agent workflows, tool use, and orchestration में भरोसेमंद काम करता है। यह तब व्यावहारिक विकल्प है जब गुणवत्ता, गति और लागत महत्वपूर्ण हो, खासकर उन टीमों के लिए जिन्हें स्थिर output,

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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