Mistral: Mistral Nemo
Mistral AI • LLM
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,...
Specifications
Context Window
131K tokens
Input Price/1M
$0.02
Output Price/1M
$0.03
Parameters
—
Max Output
16K tokens
Information
- Release date
- July 19, 2024
- Tool Calling
- ✅ Supported
- Vision
- ❌ Not supported
- Audio
- ❌ Not supported
Full Analysis: Mistral: Mistral Nemo
What is Mistral: Mistral Nemo?
Mistral: Mistral Nemo is an AI model developed by Mistral AI, classified as a large language model (LLM). It focuses on text processing and natural language generation. As an open source model, it is available for download, customization, and on-premises deployment. With a context window of 131K tokens, it is suitable for processing long documents such as contracts, books, and complete codebases.
Pricing & Costs in 2026
Mistral: Mistral Nemo is usage-based, priced at $0.02/1M input tokens and $0.03/1M output tokens. For context: 1 million tokens is approximately 750,000 words, or about 10 average-length books. At this aggressive price point, it is one of the most cost-effective options on the market, ideal for high-volume applications like chatbots, bulk document analysis, and automation.
Benchmarks & Performance
We don't have detailed benchmark results for Mistral: Mistral Nemo yet. Benchmarks are updated weekly as new data becomes available from sources like Artificial Analysis, LM Arena, and LiveBench.
It's important to note that benchmarks measure specific aspects and don't capture the full user experience. Factors like instruction adherence, behavior in long conversations, and real-world task quality vary significantly between models and aren't always reflected in standard scores.
Recommended Use Cases
Mistral: Mistral Nemo is suitable for a wide range of AI applications: long document analysis (contracts, legal proceedings, codebases), automation with tool calling (API integration, databases, external systems), high-volume chatbots and automated support, text generation, summarization, translation, and general assistance.
Comparison with Alternatives
In the 2026 AI model ecosystem, Mistral: Mistral Nemo competes directly with similarly capable models. Mistral AI competes in this segment against OpenAI, Anthropic, Google, and Meta. The choice between models depends on the specific use case, budget, latency requirements, and need for features like multimodality and tool calling.
For a detailed side-by-side comparison, use our comparison tool or check the overall model ranking.
Frequently Asked Questions
What is Mistral: 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,...
How much does Mistral: Mistral Nemo cost?
Mistral: Mistral Nemo costs $0.02/1M input tokens and $0.03/1M output tokens. For heavy usage (e.g., a chatbot handling 100k messages/month), costs can range from $10 to $1,000 depending on volume.
How does Mistral: Mistral Nemo compare with other models?
We don't have detailed benchmarks for Mistral: Mistral Nemo yet. Check the main benchmark page to compare available models.
Is Mistral: Mistral Nemo open source?
Yes, Mistral: Mistral Nemo is an open source model. You can deploy it on-premises, customize it via fine-tuning, and maintain full control over your data. Check the official repository for the specific license.
What is Mistral: Mistral Nemo best for?
Mistral: Mistral Nemo excels at general-purpose language tasks. With its large context window, it handles long documents, codebases, and extended conversations. It supports tool calling for API integrations and automation.
Last updated: June 01, 2026 • View methodology →