Mistral Small (24B) Instruct 25.01
Fast. Efficient. Production-Ready.
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.
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
import requestsresponse = requests.post("https://modelslab.com/api/v7/llm/chat/completions",json={"key": "YOUR_API_KEY","prompt": "","model_id": ""})print(response.json())
Ready to create?
Start generating with Mistral Small (24B) Instruct 25.01 on ModelsLab.