Mistral Nemo overview
Mistral Nemo by Mistral AI
Explore Mistral-Nemo, a cutting-edge language model designed for high-performance NLP tasks with extensive multilingual support.
Mistral Nemo specs
- Model ID
mistralai/mistral-nemo- Developer
- Mistral AI
- Context window
- 128,000 tokens
- Max output
- 16,384 tokens
- Input
- Text
- Output
- Text
- API
- OpenAI-compatible, base URL
https://api.aimlapi.com/v1
Basic Information
- Developer/Creator: Mistral AI and NVIDIA
- Model Type: Large Language Model (LLM)
Overview:
Mistral-Nemo is a state-of-the-art large language model designed for advanced natural language processing tasks, including text generation, summarization, translation, and sentiment analysis. It features a large context window of up to 128k tokens, making it suitable for handling extensive inputs and complex tasks.
Key Features:
- 12 billion parameters for robust performance.
- Supports a context window of up to 128k tokens.
- Instruction-tuned for improved task performance and adherence to prompts.
- Multilingual capabilities covering over 10 languages including English, French, Spanish, and Chinese.
- Utilizes the Tekken tokenizer for efficient text and code compression.
Intended Use:
Mistral-Nemo is designed for applications requiring high-quality text generation, such as chatbots, content creation tools, document summarization, and multilingual communication solutions.
Language Support:
The model supports multiple languages, making it versatile for global applications.
Architecture:
Mistral-Nemo is built on a Transformer architecture with the following specifications:
- Grouped Query Attention and Sliding Window Attention techniques are employed to enhance performance.
Use cases
- Long-form Reasoning: Complex documents, long-span Q&A
- Code Generation & Debugging: Reliable multi-turn programming assistance
- Multilingual Agents: Supports 10+ languages including Chinese, Arabic, Hindi
- RAG & Analytics: Handles large contexts in retrieval pipelines
- Math & Logic Tasks: High accuracy on benchmarks like HellaSwag, Winogrande
Capabilities
- Function calling
- Streaming
- Structured outputs
Mistral Nemo API pricing
| Usage | Price | Unit |
|---|---|---|
| Input | $0.1587 | 1M tokens |
| Output | $0.1799 | 1M tokens |
| Cached input | $0.1587 | 1M tokens |
Prices from the AI/ML API price list, checked on Nov 4, 2026.
Mistral Nemo vs other models: token prices
AI/ML API input and output rates for 5 models, per million tokens.
| Model | Input | Output |
|---|---|---|
 Mistral Nemo | $0.1587 | $0.1799 |
 Hy-MT2-1.8B | $0.0466 | $0.1873 |
| Small 4 | $0.1984 | $0.7935 |
| Mistral Large 4 | $1.36 | $4.18 |
| Medium 3.5 | $1.59 | $7.93 |
How to use the Mistral Nemo API
View docs
Build with your agent
Give your agent the model details, code and documentation.
1Get your API key
Create API keyexport AIMLAPI_KEY="8f2b4c7d9a1e6b3f…"2Make your first request
curl 'https://api.aimlapi.com/v1/chat/completions' \
-H "Authorization: Bearer $AIMLAPI_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "mistralai/mistral-nemo",
"messages": [
{
"role": "user",
"content": "Write a haiku about the ocean."
}
]
}'import os
import requests
headers = {
"Authorization": f"Bearer {os.environ['AIMLAPI_KEY']}",
"Content-Type": "application/json",
}
payload = {
"model": "mistralai/mistral-nemo",
"messages": [
{
"role": "user",
"content": "Write a haiku about the ocean."
}
]
}
response = requests.post("https://api.aimlapi.com/v1/chat/completions", headers=headers, json=payload, timeout=120)
response.raise_for_status()
print(response.json())const response = await fetch("https://api.aimlapi.com/v1/chat/completions", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.AIMLAPI_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"model": "mistralai/mistral-nemo",
"messages": [
{
"role": "user",
"content": "Write a haiku about the ocean."
}
]
}),
});
if (!response.ok) throw new Error(`HTTP ${response.status}`);
console.log(await response.json());Models similar to Mistral Nemo
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Mistral Nemo FAQ
What is the context window of Mistral Nemo?
Mistral Nemo has a 128,000 tokens context window and can return up to 131,072 tokens.
What inputs and outputs does Mistral Nemo support?
Mistral Nemo takes text as input and returns text.
What is the model ID for Mistral Nemo?
Use mistralai/mistral-nemo as the model id. Requests go to https://api.aimlapi.com/v1/chat/completions.
When was Mistral Nemo released?
Mistral Nemo became available on September 9, 2025.
How much does Mistral Nemo cost?
Mistral Nemo costs $0.1587 input and $0.1799 output per 1M tokens on AI/ML API, billed as you go with no subscription.
Does Mistral Nemo support streaming?
Yes, Mistral Nemo can stream responses as they are generated.
Who created Mistral Nemo?
Mistral Nemo was built by Mistral AI.