minimax-m2.5MiniMax
- api
- chat
- hosting
- Singapore
- model lab
- MiniMax
- weights
- open
- added
- February 2026
- model id
- minimaxi/minimax-m2.5
capabilities 4/8
4 providers serve minimax-m2.5. This page is one of them. Compare all endpoints
- input
- $0.30
- output
- $1.20
- cache write
- $1.20
- cache read
- $0.06
worked cost
| volume | cost |
|---|---|
| 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
no measured traffic for this endpoint yet. pricing above is the provider's own
| eval | Score as a share of 100 | /100 |
|---|---|---|
| τ²-Bench | 95.3 | |
| GPQA Diamond | 84.8 | |
| Terminal-Bench Hard | 34.8 | |
| Intelligence Index | 22.8 | |
| Humanity's Last Exam | 20.5 | |
| 5 evals | mean | 51.6 |
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 2026-02-12.
- 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.
minimaxi/minimax-m2.5this id pins the minimax deployment, with no routing and no failover. the managed id on the canonical page routes across all 4 providers instead
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-m2.5", 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
MiniMax-M2.5 is a SOTA large language model designed for real-world productivity. Trained in a diverse range of complex real-world digital working environments, M2.5 builds upon the coding expertise of M2.1 to extend into general office work, reaching fluency in generating and operating Word, Excel, and Powerpoint files, context switching between diverse software environments, and working across different agent and human teams. Scoring 80.2% on SWE-Bench Verified, 51.3% on Multi-SWE-Bench, and 76.3% on BrowseComp, M2.5 is also more token efficient than previous generations, having been trained to optimize its actions and output through planning.
questions 6
How much does minimax-m2.5 cost?
What is the context window of minimax-m2.5?
How does minimax-m2.5 perform on benchmarks?
What can minimax-m2.5 do?
How do I use minimax-m2.5 with the OpenAI SDK?
Can I run minimax-m2.5 through Requesty?
more from minimax 5
| endpoint | ctx | in /M |
|---|---|---|
| minimax-m3 | 1M | $0.30 |
| minimax-m2.7-highspeed | 200K | $0.60 |
| minimax-m2.7 | 200K | $0.30 |
| minimax-m2.5-highspeed | 200K | $0.60 |
| minimax-m2 | 200K | $0.30 |
call minimax-m2.5 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