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minimax-m2.7MiniMax

from /1M in$0.30minimax
context200K128K out
providers21 region
endpoints21 region
endpoints
2
regions
1
api
chat
released
March 2026

capabilities 4/8

visionreasoningtoolscachingweb searchjson schemacomputer useimage gen

endpoints

2 / 1 region
Providers serving minimax-m2.7, with pricing and measured performance. Best value in each column is coloured.
#flags
1MiniMaxGlobal200K$0.30$1.20$0.06zdr
2Novita AIGlobal200K$0.30$1.20$0.06zdr
provider price, no markupper 1M tokensblank where no qualifying sample

measured

through Sep 12

no measured traffic for this model yet. the endpoints table above carries provider pricing

benchmarks

artificial analysis
Benchmark scores, each normalised to 100
evalScore as a share of 100/100
GPQA Diamond87.4
τ²-Bench84.8
Coding Index52.6
SciCode50.1
Terminal-Bench Hard39.4
Humanity's Last Exam29.6
Intelligence Index23.2
7 evalsmean52.4

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 2026-03-18.

call it

model=
minimax-m2.7

requesty routes this id across every provider serving minimax-m2.7, picking on price and health and failing over automatically. the id stays valid when a provider changes underneath it

Base url is https://router.requesty.ai/v1 for every id here. One key reaches the whole catalog.

quickstart

openai compatible
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="minimax-m2.7",    messages=[        {"role": "user", "content": "Explain quantum computing in one paragraph."},    ],) print(response.choices[0].message.content)

Change the base url, use your Requesty key, set the model to any id in the call pane. Existing OpenAI SDK code needs no other edit, and the same key reaches every other model in the catalog, so switching later is a one-parameter change. Browse all models

notes

reference

MiniMax-M2.7 is a next-generation large language model designed for autonomous, real-world productivity and continuous improvement. Built to actively participate in its own evolution, M2.7 integrates advanced agentic capabilities through multi-agent collaboration, enabling it to plan, execute, and refine complex tasks across dynamic environments. Trained for production-grade performance, M2.7 handles workflows such as live debugging, root cause analysis, financial modeling, and full document generation across Word, Excel, and PowerPoint. It delivers strong results on benchmarks including 56.2% on SWE-Pro and 57.0% on Terminal Bench 2, while achieving a 1495 ELO on GDPval-AA, setting a new standard for multi-agent systems operating in real-world digital workflows.

questions 6

Which providers serve minimax-m2.7?
minimax-m2.7 is available from 2 providers through Requesty: MiniMax, Novita AI. All endpoints share one OpenAI-compatible API and one key, and Requesty fails over between them automatically.
How much does minimax-m2.7 cost?
Pricing starts at $0.30 per million input tokens and $1.20 per million output tokens on the cheapest provider. Prices vary by provider and region; the table above shows every endpoint. Requesty charges exactly what the upstream provider charges, with no markup.
Is minimax-m2.7 open weights?
Yes. minimax-m2.7 is an open-weights model from MiniMax, which is why multiple inference providers can host it. Provider choice affects price, latency, and data-privacy terms, all compared above.
What is the context window of minimax-m2.7?
minimax-m2.7 supports up to 200K tokens of context, with up to 128K output tokens per response. Some providers expose a smaller window; check the per-endpoint context column above.
How do I use minimax-m2.7 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 "minimax-m2.7" or any endpoint id from the table above. The quickstart section shows Python, JavaScript and cURL snippets.
Should I call minimax-m2.7 by its managed id or a provider id?
Use the managed id, "minimax-m2.7". Requesty picks which of the 2 providers serves each request based on price and health, and fails over when one degrades, so the id keeps working while the routing changes underneath it. Send a provider id like "minimaxi/minimax-m2.7" only when you need one specific deployment and want no failover.

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route minimax-m2.7 through one endpoint

One key for 2 providers on this model and 600+ others. No markup on provider prices, automatic failover, caching built in. Weekly aggregates in the measured pane come from production traffic routed through Requesty, one line per provider on a shared axis. Methodology

minimax-m2.72 providers2 endpointsfrom $0.30 /1M inctx 200Kupdated Sep 12