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minimax-m2MiniMax

in /1M$0.30input tokens
out /1M$1.20output tokens
context200K128K out
trainingnoon your prompts
api
chat
hosting
Singapore
model lab
MiniMax
weights
open
added
October 2025
model id
minimaxi/minimax-m2

capabilities 3/8

visionreasoningtoolscachingweb searchjson schemacomputer useimage gen

pricing

no markup
input
$0.30
output
$1.20
cache write
-
cache read
-

worked cost

Estimated cost for three request volumes
volumecost
100K in + 10K out$0.0420
1M in + 100K out$0.42
10M in + 1M out$4.20

Requesty charges what the upstream provider charges, with no markup and no per-request fee. Prompt caching and smart routing cut the effective cost further on repeated context. Gateway pricing

provider price, passed throughper 1M tokens

measured

through Sep 12

no measured traffic for this endpoint yet. pricing above is the provider's own

benchmarks

artificial analysis
Benchmark scores, each normalised to 100
evalScore as a share of 100/100
τ²-Bench86.8
LiveCodeBench82.6
MMLU Pro82.0
Math Index78.3
AIME 202578.3
GPQA Diamond77.7
Terminal-Bench Hard25.8
Intelligence Index18.6
Humanity's Last Exam13.7
9 evalsmean60.4

Scores from Artificial Analysis and public leaderboards, normalised to 100. Bar colour is the band, not the rank: green 80 and up, blue 55 and up, amber 30 and up. Benchmarks measure narrow skills, so test on your own workload before committing. Released 2025-10-26.

policy

data terms
retention
none
trains on prompts
no
hosted in
Singapore

Terms are the provider's, not Requesty's: routing a request here puts it under them. MiniMax Privacy Policy

Need every request to stay in one jurisdiction? EU hosting routes only through EU-hosted providers.

quickstart

openai compatible
minimaxi/minimax-m2

this id pins the minimax deployment, with no routing and no failover. the managed id on the canonical page routes across all 1 providers instead

main.py
from openai import OpenAI client = OpenAI(    api_key="YOUR_REQUESTY_API_KEY",    base_url="https://router.requesty.ai/v1",) response = client.chat.completions.create(    model="minimaxi/minimax-m2",    messages=[        {"role": "user", "content": "Explain quantum computing in one paragraph."},    ],) print(response.choices[0].message.content)

Change the base url to https://router.requesty.ai/v1, use your Requesty key, set the model to the id above. Existing OpenAI SDK code needs no other edit, and the same key reaches every other model in the catalog. Browse all models

notes

reference

MiniMax-M2 is a compact, high-efficiency large language model optimized for end-to-end coding and agentic workflows. With 10 billion activated parameters (230 billion total), it delivers near-frontier intelligence across general reasoning, tool use, and multi-step task execution while maintaining low latency and deployment efficiency.

questions 6

How much does minimax-m2 cost?
minimax-m2 is priced at $0.30 per million input tokens and $1.20 per million output tokens when accessed via Requesty. Requesty charges exactly what the upstream provider charges, we don't add markup.
What is the context window of minimax-m2?
minimax-m2 has a context window of 200K tokens, with a maximum output of 128K tokens per response. That is roughly 267 words of input you can fit in a single prompt.
How does minimax-m2 perform on benchmarks?
minimax-m2 scores 86.8% on τ²-Bench, 82.6% on LiveCodeBench, 82.0% on MMLU Pro. The benchmarks pane shows every published result, each normalised to 100.
What can minimax-m2 do?
minimax-m2 supports tool calling, extended reasoning, structured outputs (JSON schema). You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use minimax-m2 with the OpenAI SDK?
Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "minimaxi/minimax-m2". The quickstart pane shows Python, JavaScript and cURL snippets.
Can I run minimax-m2 through Requesty?
Yes. minimax-m2 runs through Requesty's OpenAI-compatible API, served from MiniMax. You do not host the model yourself: point base_url at Requesty, set the model to "minimaxi/minimax-m2", and requests are routed to the upstream provider with automatic failover. The same key gives you 600+ other models too.

more from minimax 5

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minimax-m31M$0.30
minimax-m2.7-highspeed200K$0.60
minimax-m2.7200K$0.30
minimax-m2.5200K$0.30
minimax-m2.5-highspeed200K$0.60

call minimax-m2 through one endpoint

One key for this endpoint and 600+ other models. No markup on provider prices, automatic failover when a provider degrades, and prompt caching built in. Methodology

minimax-m2minimaxin $0.30 /1Mout $1.20 /1Mctx 200Khosted Singapore