Using MiniMax-M2-240k on Fireworks AI
Implementation guide · MiniMax M2 · MiniMax
ServerlessOpen Source
Fireworks AI exposes MiniMax-M2-240k through model ID minimax-m2-240k. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-06-15. Next refresh: weekly.
Quick Start
- 1
- 2Use the Fireworks AI SDK or REST API to call
minimax-m2-240k— see the documentation for request format. - 3
Code Examples
Install
pip install openaiAPI key
FIREWORKS_API_KEYModel ID
minimax-m2-240kFireworks model IDs use "accounts/fireworks/models/{model-name}" format, e.g. "accounts/fireworks/models/llama4-scout-instruct-basic" or "accounts/fireworks/models/deepseek-r1".
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["FIREWORKS_API_KEY"],
base_url="https://api.fireworks.ai/inference/v1"
)
response = client.chat.completions.create(
model="minimax-m2-240k",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Pricing on Fireworks AI
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.30 |
| Output tokens | $1.20 |
Capabilities
No model capability flags are currently sourced.
About MiniMax-M2-240k
MiniMax-M2-240k is MiniMax's MiniMax M2 model. It offers a 240K-token context window.
Model Specs
Released2025-01-01
Parameters240B
Context240k
ArchitectureDecoder Only