Mercury: The First Commercial-Scale Language Model With Diffusion-Based Text Generation At 10X SpeedInception Labs has introduced Mercury, the first commercial-scale language model utilizing the diffusion paradigm, offering a 10x speed improvement over traditional autoregressive models while maintaining comparable quality to leading models like GPT-4o-mini and Claude 3.5 Haiku.
Ranked highly on Copilot Arena for both speed and quality, Mercury enables early adopters to enhance user experiences and reduce costs by replacing conventional LLMs. The model is compatible with existing hardware and pipelines, providing accessible solutions through API and on-premise deployments.
Mercury is the first commercial-scale language model built on the diffusion paradigm, marking a significant shift in generative AI technology. Unlike traditional autoregressive models that generate text sequentially, one token at a time, Mercury leverages parallel, coarse-to-fine generation to achieve unprecedented speed and quality. This approach not only accelerates text and code generation but also sets a new benchmark for performance in the field of large language models (LLMs).
The model has demonstrated remarkable efficiency, achieving up to 10x faster generation compared to conventional autoregressive models, as validated by independent evaluations from @Artificial Analysis. With a per-user throughput exceeding 1000 tokens per second on NVIDIA H100, Mercury matches or surpasses the performance of speed-optimized models like GPT-4o-mini and Claude 3.5 Haiku while maintaining comparable quality. These advancements have positioned Mercury as a leader in both speed and quality rankings on platforms such as Copilot Arena.
- Official site: www.inceptionlabs.ai
- Online demo: chat.inceptionlabs.ai