Using Mistral NeMo Instruct (2407) on DeepInfra
Implementation guide · Mistral NeMo · MistralAI
Quick Start
- 1
- 2Use the DeepInfra SDK or REST API to call
mistral-nemo-instruct— see the documentation for request format. - 3
Code Examples
pip install openaiDEEPINFRA_API_KEYmistral-nemo-instructDeepInfra uses "organization/model-name" format, e.g. "meta-llama/Meta-Llama-3-8B-Instruct" or "mistralai/Mistral-7B-Instruct-v0.3". See the DeepInfra model catalog for exact IDs.
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["DEEPINFRA_API_KEY"],
base_url="https://api.deepinfra.com/v1/openai"
)
response = client.chat.completions.create(
model="mistral-nemo-instruct",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)About DeepInfra
DeepInfra offers serverless AI inference with a simple API, supporting hundreds of models across text generation, embeddings, and more. Pay-per-token pricing with no upfront commitments.
DeepInfra is a cloud inference platform offering cost-effective access to open-source AI models. It provides serverless inference for leading models from Meta, Mistral, Alibaba, and others with competitive token-based pricing.
Pricing on DeepInfra
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.02 |
| Output tokens | $0.04 |
Capabilities
No model capability flags are currently sourced.
About Mistral NeMo Instruct (2407)
Mistral NeMo Instruct (2407) is MistralAI's Mistral NeMo model. It offers a 128K-token context window and scores 57.1 on GPQA.