MiniMax M2.7 is a text-only language model optimized for agentic workflows, coding, and debugging. Reach for it when you need reliable tool use and reasoning at a balanced cost tier.
Modalities
Text → Text
Below release
None reported
Weights
Published
MiniMaxAI/MiniMax-M2.7
Where it sits in the catalogue Kyma measures
Every number against every text model Kyma prices per token — a stated rule, not a chosen line-up.
$0.405
output $1.62
median $1.013 · best $0.0494
$1.62
per 1M tokens generated
median $3.531 · best $0.218
100%
147 observations since 2026-05-02
median 96.5% · best 100.0%
52 tok/s
probe median, one fixed prompt
median 36.3 tok/s · best 377.8 tok/s
5.52 s
probe median, to a complete answer
median 2.73 s · best 0.84 s
205K
max output 32,768
published by MiniMax, not measured here
Tick above each rail is this model, below it the other 70. Dashed rule is the field median, solid is its best. Better is left; the axis stops at the 90th percentile, so a few models sit past its right edge.
Usage
How much this model is actually called here.
Rank
#7
of 100 active models
Tokens served
119.8M
all-time
Platform share
2.7%
of all tokens
Pricing
Pay per token. Cached input bills at this model’s own cached rate, listed below.
+ Estimate your workload− Estimate your workload
Estimated monthly cost
$48.60
$1.62 / day on MiniMax M2.7
Same workload on:
Estimates use list pricing. Actual bills depend on real token counts, and every response includes its exact cost.
When to use MiniMax M2.7
Where this model earns its cost — and where it doesn't.
MiniMax M2.7 is a frontier-tier language model built by MiniMax for agentic productivity. It accepts text input and returns text output, with native support for tool calling, structured outputs, and explicit reasoning steps. It operates with a 204,800-token context window and a maximum output length of 32,768 tokens.
On Kyma, the model runs on an OpenAI-compatible endpoint at medium generation speed, routing automatically through failover paths if a serving instance degrades. Responses include exact token costs in the usage.cost field and identify the executed model via the X-Kyma-Model header.
The model does not support vision inputs or prompt caching. If your workflow relies on image analysis or requires cached prefix discounts, you will need to route elsewhere or structure prompts differently.
Agentic Workflow Orchestration
Handles multi-step tool calls and state tracking for autonomous agents.
Code Generation and Debugging
Writes, reviews, and fixes code across multiple languages with structured reasoning.
Productivity and Content Drafting
Generates long-form text and organizes complex information within a large context window.
Structured Data Extraction
Outputs strictly formatted JSON or XML for downstream parsing and API integration.
Not ideal for: Do not use this model for tasks requiring image understanding, multimodal input, or prompt caching discounts.
How it compares
Against the peers people actually weigh it against.
| Spec | MiniMax M2.7 | MiniMax M2.5 | MiniMax M3 |
|---|---|---|---|
| Input /1M | $0.405 | $0.405 | $0.405 |
| Output /1M | $1.62 | $1.62 | $1.62 |
| Context | 205K | 197K | 1M |
| Tools | Yes | Yes | Yes |
| Reasoning | Yes | Yes | Yes |
| Throughput | 52 tok/s | 74 tok/s | 35 tok/s |
Quick start
Up and running in under two minutes.
- 1
Create an API key
Sign up and grab a key from the dashboard — $0.50 free credit on the free tier, which covers MiniMax M2.7. No card required.
Get API key → - 2
Make your first request
Drop in your key and send a chat completion — fully OpenAI-compatible.
curl https://kymaapi.com/v1/chat/completions \ -H "Authorization: Bearer YOUR_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "minimax-m2.7", "messages": [ {"role": "user", "content": "Explain prompt caching in one paragraph."} ] }' - 3
Stream responses
Add
"stream": trueto receive tokens as they arrive.curl https://kymaapi.com/v1/chat/completions \ -H "Authorization: Bearer YOUR_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "model": "minimax-m2.7", "stream": true, "messages": [{"role": "user", "content": "Hello!"}] }'
FAQ
Common questions about this model.
What is the context window of MiniMax M2.7?
How much does the MiniMax M2.7 API cost?
Does MiniMax M2.7 support function calling?
Are the weights for MiniMax M2.7 publicly available?
Is MiniMax M2.7 ever served below the precision its creator released it at?
How do I use MiniMax M2.7?
Does this model support image inputs?
Can I use prompt caching with this model?
How do I track costs per request?
More models by MiniMax
| Model | Context | Input | Output |
|---|---|---|---|
MiniMax M3 | 1M | $0.405 | $1.62 |
MiniMax M2.5 | 197K | $0.405 | $1.62 |
MiniMax Speech Turbo | — | $0.04 / 1K char | |
MiniMax Speech HD | — | $0.07 / 1K char | |
MiniMax Image 01 | — | $0.005 / image | |
