MiniMax M-series - Upmore

The MiniMax M-series text models are available through Upmore via the standard Chat Completions API (/v1/chat/completions). All models in the series share the same request and response format — switch between them by changing the model parameter.

Available models

Model	Notes
`MiniMax-M3`	Latest generation
`MiniMax-M2.7`
`MiniMax-M2.7-highspeed`	High-speed variant of M2.7
`MiniMax-M2.5`
`MiniMax-M2.5-highspeed`	High-speed variant of M2.5
`MiniMax-M2.1`
`MiniMax-M2.1-highspeed`	High-speed variant of M2.1
`MiniMax-M2`

The -highspeed variants accept the same parameters and return the same response format as their standard counterparts. They run on faster inference infrastructure and are billed at a higher rate — pick them when latency matters more than cost.

Key capabilities

Chat Completions API — Standard /v1/chat/completions endpoint with messages
Reasoning — Thinks before answering; the chain-of-thought is returned in reasoning_content alongside the reply (budget max_tokens accordingly)
Anthropic-compatible — Also callable via /v1/messages in Claude message format
Streaming — Supports real-time token streaming via SSE
Tool use — Supports function calling and tool use

Quick example

curl https://api.upmore.net/v1/chat/completions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "MiniMax-M3",
    "messages": [
      { "role": "user", "content": "Explain quantum entanglement in simple terms." }
    ]
  }'

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://api.upmore.net/v1"
)

response = client.chat.completions.create(
    model="MiniMax-M3",
    messages=[
        {"role": "user", "content": "Explain quantum entanglement in simple terms."}
    ]
)

print(response.choices[0].message.content)

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://api.upmore.net/v1"
)

stream = client.chat.completions.create(
    model="MiniMax-M2.7-highspeed",
    messages=[
        {"role": "user", "content": "Write a short poem about the sea."}
    ],
    stream=True
)

for chunk in stream:
    if chunk.choices and chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="")

Parameters

Parameter	Type	Required	Description
`model`	string	Yes	One of the model IDs from the table above
`messages`	array	Yes	List of `{ role, content }` objects
`stream`	boolean	No	Enable SSE streaming. Default: `false`
`temperature`	float	No	Controls randomness. Default: `1`
`top_p`	float	No	Nucleus sampling threshold. Default: `1`
`max_tokens`	integer	No	Maximum output tokens to generate
`stop`	string / array	No	Sequences that stop generation
`tools`	array	No	List of tools the model may call

API Reference

View the interactive API playground.