# M2 1 Highspeed API

MiniMax's M2 1 Highspeed costs $0.601 per million input tokens and $2.403 per million output tokens from 1 independent provider. Each request through the OpenAI-compatible API goes to the offer with the lowest estimated charge that meets your rules.

- Providers compete for each request. The exchange ranks the offers that meet your rules by estimated charge. It fixes your maximum charge before the first token, and you pay for the tokens that the model uses.
- The OpenAI and Anthropic APIs. Use the OpenAI or Anthropic SDK that you have. Set the base URL and your key, and send m2-1-highspeed as the model.
- Your data rules. Send x-liquid-retention: none and only offers whose provider does not keep your content compete for the request.

## About M2 1 Highspeed

M2 1 Highspeed is a language model from MiniMax. It takes text, files and images and gives text. The largest offer takes 204,800 input tokens. 1 independent provider quotes it on this exchange now.

## Facts

- Model name: m2-1-highspeed
- Maker: MiniMax
- Context window: 204.8K tokens
- Input price: $0.601 per million tokens
- Output price: $2.403 per million tokens
- Providers: 1 independent provider
- Regions: us

## Providers

- [Architect](https://liquidinference.ai/providers/805445a7-0e40-4c1b-9baf-7b3b01e30e42.md): us, $0.601 input and $2.403 output per million tokens, $0.601 cache read per million tokens, 204.8K tokens of context

## Scores

- HLE: 23.2, #149 of 465
- GPQA: 83.0, #125 of 432
- AA-LCR: 67.7, #193 of 409
- Terminal-Bench Hard: 28.8, #110 of 311
- LiveCodeBench: 81.0, #22 of 250
- AIME 2025: 82.7, #31 of 199
- MMLU-Pro: 87.5, #10 of 253
- τ²-Bench: 85.4, #81 of 313
- IFBench: 69.9, #65 of 321

Scores: Artificial Analysis (https://artificialanalysis.ai/)

## Request

```sh
curl https://router.inference.ai.exchange/v1/chat/completions \
  -H "Authorization: Bearer $LIQUID_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "m2-1-highspeed",
    "messages": [{"role":"user","content":"Say hello."}]
  }'
```

## Questions

### What is M2 1 Highspeed?

M2 1 Highspeed is a language model from MiniMax.

### How much does M2 1 Highspeed cost?

Offers now ask $0.601 per million input tokens and $2.403 per million output tokens. A job pays for the tokens it uses. The exchange picks the cheapest eligible offer.

### What is the context length of M2 1 Highspeed?

The largest offer takes 204,800 input tokens. A smaller offer can take less. The exchange skips an offer that cannot take your message.

### What can M2 1 Highspeed do?

Its providers list Documents, Vision, Reasoning effort, JSON object, JSON schema, Frequency penalty, Logit bias, Log probabilities, Min-p sampling, Presence penalty, Repetition penalty, Seed, Stop sequences, Top-k sampling, Top-p sampling, Text, Tools.

### What inputs and outputs does M2 1 Highspeed support?

Text · Files · Images → Text.

### Which providers serve M2 1 Highspeed?

1 independent provider quote it now, with 1 offer. The table above ranks them by the cost of a typical job.

### How do I call M2 1 Highspeed?

Send "m2-1-highspeed" as the model in an OpenAI or Anthropic request. The API section links to setup steps for each client.

### When was M2 1 Highspeed listed?

The exchange first listed it on 10/10/2026. This is not its release date.

## Related pages

- [This page in a browser](https://liquidinference.ai/models/m2-1-highspeed)
- [MiniMax M3.1 Flash](https://liquidinference.ai/models/MiniMax-M3.1-Flash.md)
- [MiniMax 01](https://liquidinference.ai/models/minimax-01.md)
- [M2](https://liquidinference.ai/models/m2.md)
- [MiniMax Latest](https://liquidinference.ai/models/minimax-latest.md)
- [MiniMax M2.1](https://liquidinference.ai/models/MiniMax-M2.1.md)
- [MiniMax m3:thinking](https://liquidinference.ai/models/MiniMax-M3%3Athinking.md)
- [Set up a client](https://liquidinference.ai/connect/m2-1-highspeed)
- [All models](https://liquidinference.ai/models)
- [Providers](https://liquidinference.ai/providers.md)
- [Discover the best model for your budget](https://liquidinference.ai/discover)
- [Quickstart](https://liquidinference.ai/docs/quickstart.md)
- [llms.txt: the index of every page, as Markdown](https://liquidinference.ai/llms.txt)
- [llms-full.txt: every page in one file](https://liquidinference.ai/llms-full.txt)