Inception Labs Releases Mercury 3: Self-Tests Claim 4x to 8x Faster Than GPT-6 Luna
Inception Labs launches Mercury 3, a diffusion-based language model that the company claims significantly outperforms mainstream models in speed, targeting latency-sensitive applications.
US AI startup Inception Labs released Mercury 3 on October 21, 2026, a language model based on diffusion technology. Unlike traditional autoregressive models that generate text word by word, Mercury 3 first creates a rough draft and then refines it step by step, allowing for parallel token processing.
According to The Decoder, Inception Labs claims in internal benchmarks that Mercury 3 generates over 1,000 tokens per second on Nvidia GPUs, running four to eight times faster than OpenAI's GPT-6 Luna and Anthropic's Claude Haiku 5.5. It leads rivals in eight of 12 tests, particularly in instruction following (scoring 76.84 on IFBench) and autonomous coding (scoring 51.08 on SWE-Bench Atlas). However, Claude Haiku 5.5 wins the longer coding test DeepSWE, and GPT-6 Luna edges ahead in some Artificial Analysis tests.
The model supports a context window of up to 1 million tokens and offers an OpenAI-compatible API. Inception Labs states that Mercury 3 is designed for latency-critical applications such as autonomous AI agents, smart glasses search, and real-time customer support. Early partner Octen AI reported that median response time for smart glasses search dropped to 0.9 seconds with Mercury 3, noting that the language model was previously the bottleneck.
It is important to note that no independent third-party verification of these performance claims exists yet. Inception Labs indicates that Mercury 3 has more than 40 times the parameters of its predecessor Mercury 1 but runs at similar speeds, suggesting that diffusion models scale effectively like standard language models. The exact parameter count remains undisclosed.