MiniMax-M2.7-highspeed
Pricing & Specs

MiniMax · $0.6 input / $2.4 output per 1M tokens · 196.608K context window

$0.6
per 1M input tokens
$2.4
per 1M output tokens
196.608K
context window (tokens)

The per-token price never tells the full story. A typical task (1K input + 500 output tokens) on MiniMax-M2.7-highspeed costs about $0.0018 — roughly $1.80 per 1,000 runs. But if it needs 3x the tokens of a cheaper model to match quality on YOUR task, the economics flip. The only way to know is to benchmark it on your actual workload.

MiniMax-M2.7-highspeed API Pricing

TokensPrice
Input$0.6 / 1M tokens
Output$2.4 / 1M tokens
Cached input$0.06 / 1M tokens

Cached input tokens are billed when caching is enabled.

What that means in practice

1x One typical task (1K input + 500 output tokens): $0.0018
1K 1,000 runs of that task: $1.80
💡 Real cost depends on how verbose the model is on YOUR prompts — benchmark to measure actual tokens, not estimates.

MiniMax-M2.7-highspeed Specs

SpecValue
Context window196.608K tokens
Max output tokens128K tokens
Input modalitiestext
Output modalitiestext
Reasoning modelYes
Tool / function callingYes
JSON modeYes
StreamingYes
Prompt cachingYes
Batch APINo

FAQ

How much does MiniMax-M2.7-highspeed cost?

MiniMax-M2.7-highspeed costs $0.6 per 1M input tokens and $2.4 per 1M output tokens ($0.06 per 1M cached input tokens).

What is MiniMax-M2.7-highspeed's context window?

MiniMax-M2.7-highspeed has a 196.608K-token context window. Maximum output is 128K tokens.

Can I test MiniMax-M2.7-highspeed on my own task?

Yes. OpenMark lets you benchmark MiniMax-M2.7-highspeed against 100+ models on your own task with real API calls — no API keys needed, free tier available.

Is MiniMax-M2.7-highspeed the right model for YOUR task?

Pricing tables can't answer that. Benchmark it against 100+ models
on your actual workload — real API calls, real costs. Free tier available.

Benchmark MiniMax-M2.7-highspeed — Free →