California-based AI research and product company Inception has unveiled Mercury 3, its latest diffusion language model, claiming it outperforms speed-optimized rivals GPT-6 Luna and Claude Haiku 5.5 on a range of benchmarks while running four to eight times faster.

The new model generates more than 1,000 tokens per second on widely available NVIDIA GPUs and supports a context window of 1 million tokens, allowing it to process substantially larger amounts of information in a single request.

According to Inception, Mercury 3 is more than 40 times larger than its first-generation model, Mercury 1, while maintaining comparable processing speeds.

The company says the results demonstrate that diffusion-based language models can become more capable without sacrificing the speed advantages of their underlying architecture.

Traditional large language models generate text sequentially, predicting one token at a time. Diffusion language models take a different approach, generating and refining multiple tokens in parallel.

This allows them to produce responses faster, potentially reducing delays in applications that require frequent interactions with a model.

However, developers have traditionally faced a trade-off between model capability and response speed. Smaller models generally respond faster, while more capable systems often require additional processing time.

Inception says Mercury 3 addresses this challenge by delivering performance comparable to or better than recently released OpenAI and Anthropic models across several standard benchmarks while maintaining inference speeds above 1,000 tokens per second.

1/4 Today, we’re releasing Mercury 3. Mercury 3 is by far our most powerful model and the most intelligent diffusion LLM ever released.

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