--- title: Inception: Mercury — Fast Reasoning LLM | ModelsLab description: Generate high-quality text at 1000+ tokens/sec with Inception: Mercury. Try diffusion-based reasoning for low-latency apps via API. url: https://modelslab.com/inception-mercury canonical: https://modelslab.com/inception-mercury type: website component: Seo/ModelPage generated_at: 2026-04-15T02:01:02.274199Z --- Available now on ModelsLab · Language Model Inception: Mercury Reasoning at 1000 Tokens/Sec --- [Try Inception: Mercury](/models/open_router/inception-mercury) [API Documentation](https://docs.modelslab.com) Build Faster AI Apps --- Diffusion Core ### Parallel Token Generation Refines token groups simultaneously for 5-10x speed over autoregressive LLMs. Tunable Reasoning ### Low to High Effort Set reasoning levels from instant to high for optimized latency in voice agents. 128K Context ### Native Tool Use Supports schema-aligned JSON and tool integration as drop-in LLM replacement. Examples See what Inception: Mercury can create --- Copy any prompt below and try it yourself in the [playground](/models/open_router/inception-mercury). Code Review “Review this Python function for bugs and optimize for speed: def fibonacci(n): if n <= 1: return n return fibonacci(n-1) + fibonacci(n-2)” JSON Schema “Generate a schema-aligned JSON response listing top 5 Python libraries for data analysis with descriptions.” Agent Workflow “Plan a retrieval-augmented generation workflow using vector search and tool calls for querying customer data.” Reasoning Chain “High reasoning: Solve this logic puzzle step-by-step: Three houses in a row, owners A B C drink water milk tea, own cat dog bird.” For Developers A few lines of code. 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 ```

import requests

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

``` FAQ Common questions about Inception: Mercury --- [Read the docs ](https://docs.modelslab.com) ### What is Inception: Mercury model? ### How fast is inception mercury LLM? ### What makes Inception: Mercury unique? ### Does inception: mercury model support tools? ### Where to access Inception: Mercury LLM? ### What are benchmarks for inception mercury? Ready to create? --- Start generating with Inception: Mercury on ModelsLab. [Try Inception: Mercury](/models/open_router/inception-mercury) [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*