Using Mistral NeMo (2407) on Fireworks AI
Implementation guide · Mistral NeMo · MistralAI
Fireworks AI exposes Mistral NeMo (2407) through model ID mistral-nemo. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-06-01. Next refresh: weekly.
Quick Start
- 1
- 2Use the Fireworks AI SDK or REST API to call
mistral-nemo— see the documentation for request format. - 3
Code Examples
pip install openaiFIREWORKS_API_KEYmistral-nemoFireworks 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="mistral-nemo",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Pricing on Fireworks AI
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.20 |
| Output tokens | $0.20 |
Capabilities
No model capability flags are currently sourced.
About Mistral NeMo (2407)
Mistral NeMo is a 12B parameter open-source language model developed by Mistral AI, designed for efficient performance and reasoning tasks. With a 128K token context window, it excels at handling long documents and complex reasoning. The model is optimized for fast inference while maintaining strong performance across multiple benchmarks, making it suitable for enterprise deployments where balance between performance and resource efficiency is critical.