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mistral
mistralai/mistral-nemo

mistralai/mistral-nemo

131,072 context · $0.03/M input tokens · $0.06/M output tokens

A 12B parameter model with a 128k token context length built by Mistral in collaboration with NVIDIA. The model is multilingual, supporting English, French, German, Spanish, Italian, Portuguese, Chinese, Japanese,...

Pricing

Pay-per-use

No upfront costs, pay only for what you use

Input$0.03 / M Tokens
Output$0.06 / M Tokens

Try the model

mistralai/mistral-nemo
Online
mistral
Hi! I am a helpful AI assistant. What can I do for you?

API Usage

Use the following code examples to integrate with our API:

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://llm.wavespeed.ai/v1"
)

response = client.chat.completions.create(
    model="mistralai/mistral-nemo",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

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

Model Introduction

Mistralai mistral-nemo

mistralai mistral-nemo


Why It Looks Great

  • Large Language Model architecture for efficient processing
  • 131072 context window for long document handling
  • Competitive pricing at $0.0/$0.0 per million tokens

Key Features

  • Context Window: 131072 tokens
  • Max Output: 16384 tokens
  • Vision: Supported
  • Function Calling: Supported

Specifications

SpecificationValue
ProviderMistralai
Model TypeLarge Language Model (LLM)
ArchitectureN/A
Context Window131072 tokens
Max Output16384 tokens
InputText
OutputText
VisionSupported
Function CallingSupported

Pricing

Token TypeCost per Million Tokens
Input$0.0
Output$0.0

How to Use

  1. Write your prompt — describe the task, provide context, and specify desired output format.
  2. Submit — the model processes your request and returns the response.

API Integration

Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: mistralai/mistral-nemo


API Usage

Python SDK

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://llm.wavespeed.ai/v1"
)

response = client.chat.completions.create(
    model="mistralai/mistral-nemo",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

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

cURL

curl https://llm.wavespeed.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "mistralai/mistral-nemo",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Notes

  • Model: mistralai/mistral-nemo
  • Provider: Mistralai

Info

Providermistral
Typellm

Supported Functionality

Input
Text
Output
Text
Context131,072
Max Output16,384
Vision-
Function Calling✓ Supported

API Access Guide

Base URLhttps://llm.wavespeed.ai/v1
API Endpointchat/completions
Model IDmistralai/mistral-nemo

Mistral Nemo API

mistralai/mistral-nemo

A 12B parameter model with a 128k token context length built by Mistral in collaboration with NVIDIA. The model is multilingual, supporting English, French, German, Spanish, Italian, Portuguese, Chinese, Japanese,...

Input

$0.025 /M

Output

$0.055 /M

Context

131K

Max Output

16K

Tool Use

Supported

Try Mistral Nemo on WaveSpeedAI

Access Mistral Nemo through our unified API — OpenAI-compatible, no cold starts, transparent pricing.

Frequently Asked Questions about Mistral Nemo

How much does Mistral Nemo cost via the API?+

Pricing on WaveSpeedAI: $0.03 per million input tokens and $0.06 per million output tokens. Prompt caching and batch processing are billed separately and reduce effective cost on long, repetitive workloads.

What is the context window of Mistral Nemo?+

Mistral Nemo supports up to 131K tokens of context with up to 16K tokens of output per request.

Is Mistral Nemo OpenAI-compatible?+

Yes. WaveSpeedAI exposes Mistral Nemo through an OpenAI-compatible endpoint at https://llm.wavespeed.ai/v1. Point the official OpenAI SDK at this base URL with your WaveSpeedAI API key — no other code changes required.

How do I get started with Mistral Nemo?+

Sign in to WaveSpeedAI, create an API key in Access Keys, then send a request to https://llm.wavespeed.ai/v1/chat/completions with model id set to the value shown above. New accounts receive free credits to evaluate Mistral Nemo before paying per token.

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