---
title: Mistral Small 24B Instruct 2501 — Fast LLM | ModelsLab
description: Deploy Mistral Small 24B Instruct 2501 for fast, accurate responses. 24B parameters, 32k context, 150 tokens/sec. Try now.
url: https://modelslab.com/mistral-small-24b-instruct-2501
canonical: https://modelslab.com/mistral-small-24b-instruct-2501
type: website
component: Seo/ModelPage
generated_at: 2026-04-15T00:25:49.583405Z
---

Available now on ModelsLab · Language Model

Mistral Small (24B) Instruct 25.01
Fast. Efficient. Production-Ready.
---

[Try Mistral Small (24B) Instruct 25.01](/models/mistral_ai/mistralai-Mistral-Small-24B-Instruct-2501) [API Documentation](https://docs.modelslab.com)

Built For Speed And Accuracy
---

Lightning-Fast Inference

### 150 Tokens Per Second

Delivers 81% MMLU accuracy with ultra-low latency for real-time applications.

Compact Architecture

### 24B Parameters, Full Power

Runs on single GPU or 32GB Mac. Competes with models three times its size.

Extended Context

### 32K Token Window

Process longer documents and conversations without losing context or quality.

Examples

See what Mistral Small (24B) Instruct 25.01 can create
---

Copy any prompt below and try it yourself in the [playground](/models/mistral_ai/mistralai-Mistral-Small-24B-Instruct-2501).

Customer Support Agent

“You are a helpful customer support assistant. Answer questions about product features, pricing, and troubleshooting. Keep responses concise and professional. User question: How do I reset my password?”

Code Review

“Review this Python function for bugs and performance issues. Suggest improvements and explain your reasoning. Function: def calculate\_total(items): total = 0; for item in items: total = total + item\['price'\] \* item\['quantity'\]; return total”

Content Summarization

“Summarize the following article in 3 bullet points, focusing on key takeaways. Article: \[paste technical documentation or blog post\]”

Multi-Language Translation

“Translate the following English text to Spanish, French, and German. Maintain formal tone. Text: The quarterly earnings report shows a 15% increase in revenue.”

For Developers

A few lines of code.
Fast inference. Three lines.
---

ModelsLab handles the infrastructure: fast inference, auto-scaling, and a developer-friendly API. No GPU management needed.

- **Serverless:** scales to zero, scales to millions
- **Pay per token,** no minimums
- **Python and JavaScript SDKs,** plus REST API

[API Documentation ](https://docs.modelslab.com)

PythonJavaScriptcURL

Copy

```
<code>import requests

response = requests.post(
    "https://modelslab.com/api/v7/llm/chat/completions",
    json={
  "key": "YOUR_API_KEY",
  "prompt": "",
  "model_id": ""
}
)
print(response.json())</code>
```

FAQ

Common questions about Mistral Small (24B) Instruct 25.01
---

[Read the docs ](https://docs.modelslab.com)

### What is Mistral Small 24B Instruct 2501?

### How does Mistral Small 24B Instruct 2501 compare to larger models?

### What are the best use cases for this model?

### Can I run Mistral Small 24B Instruct 2501 locally?

### What is the context window size?

### Is Mistral Small 24B Instruct 2501 open source?

Ready to create?
---

Start generating with Mistral Small (24B) Instruct 25.01 on ModelsLab.

[Try Mistral Small (24B) Instruct 25.01](/models/mistral_ai/mistralai-Mistral-Small-24B-Instruct-2501) [API Documentation](https://docs.modelslab.com)

---

*This markdown version is optimized for AI agents and LLMs.*

**Links:**
- [Website](https://modelslab.com)
- [API Documentation](https://docs.modelslab.com)
- [Blog](https://modelslab.com/blog)

---
*Generated by ModelsLab - 2026-04-15*