---
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-frontend-v2-927501783998.us-east4.run.app/mistral-small-24b-instruct-2501
canonical: https://modelslab-frontend-v2-927501783998.us-east4.run.app/mistral-small-24b-instruct-2501
type: website
component: Seo/ModelPage
generated_at: 2026-05-13T10:31:41.929380Z
---

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?

Mistral Small 24B Instruct 2501 is a 24-billion parameter instruction-tuned language model optimized for low-latency text generation. It achieves performance in its category while maintaining exceptional speed and efficiency.

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

Despite having 24B parameters, it performs competitively with models three times its size on code, math, and general knowledge benchmarks. It delivers 150 tokens per second with 81% MMLU accuracy, making it ideal for production deployments.

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

Mistral Small 24B Instruct 2501 excels at conversational AI, code assistance, enterprise RAG, agentic systems, and multilingual tasks. It's perfect for applications requiring fast, accurate responses with minimal latency.

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

Yes. Once quantized, it fits on a single RTX 4090 GPU or a 32GB Mac, making it ideal for on-device deployment and handling sensitive data locally.

### What is the context window size?

Mistral Small 24B Instruct 2501 supports a 32k token context window, allowing it to process longer documents and maintain conversation history effectively.

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

Yes, it's released under Apache 2.0 license, permitting both commercial and non-commercial usage and modification. Both pretrained and instruction-tuned checkpoints are available.

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)

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*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)

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*Generated by ModelsLab - 2026-05-13*