minimax-m2
MiniMax/Open weights/1 provider
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.MoreLess
Which id to call
minimaxi/minimax-m2This model has no managed policy yet, so call the provider endpoint directly. Every id in the endpoints table works the same way.
From /1M input
$0.30
MiniMax
Context
200K
128K output
Endpoints
1
1 region
Regions
1
chat
Capabilities 3/8
1 endpoint / 1 region
Providers serving minimax-m2
Provider prices, per 1M tokens. Pay as you go adds 5%, or 0% on your own keys.
| Rank | Privacy | ||||||
|---|---|---|---|---|---|---|---|
| 1 | MiniMax | Global | 200K | $0.30 | $1.20 | $0.30 | zdr |
A column is blank where no qualifying sample exists, and every row links to that provider's endpoint page.
model=
Which id to call
One base url, https://router.requesty.ai/v1, and one key for every id here.
minimaxi/minimax-m2This model has no managed policy yet, so call the provider endpoint directly. Every id in the endpoints table works the same way.
OpenAI compatible
Call it in three lines
Change the base url, use your Requesty key, set the model to any id on the left. Existing OpenAI SDK code needs no other edit.
123456789101112131415from 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)
Artificial Analysis
Benchmark scores
Graduate-level physics, chemistry & biology questions designed to resist Googling.
Artificial Analysis Intelligence Index: a composite of multiple evaluations measuring overall model capability.
Scores from artificialanalysis.ai. They measure the model, not the provider, so they are the same on every endpoint above.
5
More from MiniMax
Reference
minimax-m2 questions
Which providers serve minimax-m2?
minimax-m2 is available from 1 provider through Requesty: MiniMax. All endpoints share one OpenAI-compatible API and one key, and Requesty fails over between them automatically.
How much does minimax-m2 cost?
Pricing starts at $0.30 per million input tokens and $1.20 per million output tokens on MiniMax, the cheapest endpoint. Prices vary by provider and region; the table above shows every endpoint. Those are the upstream provider rates: pay as you go adds 5% on top, or 0% if you bring your own provider keys.
Is minimax-m2 open weights?
Yes. minimax-m2 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?
minimax-m2 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 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" or any endpoint id from the table above. The quickstart section shows Python, JavaScript and cURL snippets.
Route minimax-m2 through one endpoint
One key for 1 provider on this model and 600+ others. No markup on provider prices, automatic failover, caching built in.