LLM Reference
Featherless

Using MiniMax M2.5 on Featherless

Implementation guide · MiniMax M2 · MiniMax

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Featherless exposes MiniMax M2.5 through model ID MiniMaxAI/MiniMax-M2.5. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.

Last refreshed 2026-09-24. Next refresh: weekly.

Quick Start

  1. 1
    Create an account at Featherless and generate an API key.
  2. 2
    Use the Featherless SDK or REST API to call MiniMaxAI/MiniMax-M2.5 — see the documentation for request format.
  3. 3
    You'll be billed $0.29/1M input, $1.20/1M output tokens. See full pricing.
API PortalDocumentationPricingModel Card

Code Examples

Install
pip install openai
API key
FEATHERLESS_API_KEY
Model ID
MiniMaxAI/MiniMax-M2.5

Use exact Featherless catalog id in modelProvider.providerModelId (HF-style org/name). Not interchangeable with LLM Reference slugs.

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.featherless.ai/v1",
    api_key=os.environ["FEATHERLESS_API_KEY"],
)
response = client.chat.completions.create(
    model="MiniMaxAI/MiniMax-M2.5",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(response.choices[0].message.content)

Pricing on Featherless

TypePrice (per 1M)
Input tokens$0.29
Output tokens$1.20

Capabilities

Structured Outputs

About MiniMax M2.5

MiniMax: MiniMax M2.5 (free) available via OpenRouter. Pricing: $null/1M input, $null/1M output.

Full model details →

Model Specs

Released2025-03-01
Parameters230B (10B active)
Context197k
ArchitectureDecoder Only

Also available on(5)

OpenRouter$0.15/1MTogether AI$0.30/1MVercel AI Gateway$0.30/1M
Compare all providers →

Provider

Featherless
Featherless