Inception Labs
Inception Labs is building the next generation of LLMs using diffusion-based architectures to deliver extreme speed and efficiency for production applications.
At a Glance
- Software developers
- AI research labs
- Enterprise AI teams
- Real-time application developers
AI Tools by Inception Labs
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Inception Labs
Diffusion Based LLM Platform
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Latest News
Inception Launches Mercury 2, the Fastest Reasoning LLM
Inception Raises $50M to Power Diffusion LLMs, Increasing Speed by up to 10X
Inception Emerges from Stealth with Mercury, a New Type of Diffusion-Based AI Model
Products & Services
The world's first commercial diffusion large language model (dLLM), offering high-speed text and code generation.
A production-ready reasoning diffusion LLM that utilizes parallel refinement to achieve 5x-10x speed increases over sequential models.
API platform providing developer access to diffusion-based models with OpenAI compatibility.
Market Position
Inception positions itself as the performance leader for real-time AI, offering diffusion-based models that are significantly faster and cheaper than traditional sequential LLMs from providers like OpenAI or Anthropic.
Leadership
Founders
Stefano Ermon
CEO and Co-founder. Associate Professor of Computer Science at Stanford University. Co-inventor of diffusion modeling and recognized leader in generative AI.
Aditya Grover
Co-founder. Assistant Professor of Computer Science at UCLA. Previously a research scientist at Facebook AI Research (FAIR) and PhD student at Stanford.
Volodymyr Kuleshov
Co-founder. Assistant Professor at Cornell Tech. Co-inventor of diffusion and former PhD student at Stanford under Stefano Ermon.
Executive Team
Stefano Ermon
CEO & Co-founder
Stanford Professor and co-inventor of diffusion models.
Aditya Grover
Co-founder
UCLA Professor specializing in generative modeling.
Board of Directors
Founding Story
Founded by the original inventors of diffusion modeling, Inception was started to apply parallel refinement techniques to large language models, overcoming the sequential latency bottlenecks of traditional autoregressive transformers.
Business Model
Revenue Model
API usage-based subscription model with tiered rate limits.
Pricing Tiers
200 API requests, Early access to Mercury 2
400 API requests, Standard access
2,000+ API requests, Dedicated support, custom SLAs
Target Markets
- Software developers
- AI research labs
- Enterprise AI teams
- Real-time application developers
- Real-time coding assistants
- Low-latency voice AI applications
- High-throughput customer support automation
- Production-grade reasoning tasks
- Early access developers and enterprises in the coding and voice AI sectors