Inception: Mercury Coder
Code at 1000 Tokens/Sec
Diffusion Powers Speed
Ultra-Fast Inference
1000+ Tokens per Second
Mercury Coder runs 5-10x faster than GPT-4o Mini on H100 GPUs.
Code Optimized
Matches Frontier Benchmarks
Outperforms speed-optimized LLMs like Claude 3.5 Haiku in coding tasks.
Diffusion Architecture
Parallel Token Refinement
Starts from noise, denoises entire sequences simultaneously for low latency.
Examples
See what Inception: Mercury Coder can create
Copy any prompt below and try it yourself in the playground.
Python Web Scraper
“Write a Python script using requests and BeautifulSoup to scrape article titles from a tech news site, handle pagination, and save to CSV. Include error handling and rate limiting.”
React Component
“Generate a reusable React functional component for a responsive data table with sorting, filtering, and pagination using hooks and Tailwind CSS.”
SQL Query Optimizer
“Write an optimized SQL query for a large e-commerce database to find top-selling products by category in the last month, joining sales, products, and categories tables.”
Node.js API
“Create a Node.js Express API endpoint for user authentication with JWT, bcrypt hashing, input validation, and MongoDB integration.”
For Developers
A few lines of code.
Code fast. Diffusion LLM.
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 Inception: Mercury Coder on ModelsLab.