Mistral AI ↗Released July 18, 2024

Mistral Nemo

Open Source#27 Arena Rank12B parameters

Context

128K

Input

$0.30

Key Specifications

🏆

Arena Rank

#27

📐

Context Window

128K

📥

Input Price

per 1M tokens

$0.30

📤

Output Price

per 1M tokens

$0.30

🧠

Parameters

12B

🔓

Open Source

Yes

Best For

Lightweight tasksdrop-in replacement

About Mistral Nemo

Mistral Nemo is a compact 12B parameter model co-developed by Mistral AI and Nvidia, designed as a high-performance drop-in replacement for smaller models. Despite its size, it delivers performance significantly above its weight class on coding, reasoning, and multilingual tasks. As an open-source model, it can be self-hosted on a single GPU, making it ideal for organizations with limited compute resources or strict data privacy requirements. Its small size enables fast inference and low-cost deployment while maintaining the quality standards of the Mistral model family.

Built byMistral AI↗

Pricing per 1M tokens

Input Tokens

$0.30

Output Tokens

$0.30

Compare Mistral Nemo

See how Mistral Nemo stacks up against other leading AI models

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Frequently Asked Questions

What is Mistral Nemo?▾
Mistral Nemo is a compact 12B parameter model co-developed by Mistral AI and Nvidia, designed as a high-performance drop-in replacement for smaller models. Despite its size, it delivers performance significantly above its weight class on coding, reasoning, and multilingual tasks. As an open-source model, it can be self-hosted on a single GPU, making it ideal for organizations with limited compute resources or strict data privacy requirements. Its small size enables fast inference and low-cost deployment while maintaining the quality standards of the Mistral model family.
How much does Mistral Nemo cost?▾
Mistral Nemo costs $0.30 per 1 million input tokens and $0.30 per 1 million output tokens. Pricing is based on token usage, making it cost-effective for both small and large-scale applications.
What is Mistral Nemo's context window?▾
Mistral Nemo has a context window of 128K tokens. This determines how much text the model can process in a single request — larger context windows allow the model to handle longer documents, maintain more conversation history, and reason over bigger codebases.
Is Mistral Nemo open source?▾
Yes, Mistral Nemo is open source. This means the model weights are publicly available, allowing developers and organizations to download, fine-tune, and self-host the model on their own infrastructure. Open-source models offer greater flexibility and data privacy control.
What is Mistral Nemo best for?▾
Mistral Nemo is best suited for: Lightweight tasks, drop-in replacement. These use cases leverage the model's specific strengths in terms of capability, speed, and cost-effectiveness within Mistral AI's model lineup.