Lancelot

Inception Labs has launched Mercury 2, their next generation production-ready Diffusion LLM. Mercury 2 achieves >1,000 output tokens/s with significant gains in intelligence @_inception_ai's Diffusion LLMs (“dLLMs”) use a different architecture compared to autoregressive based LLMs. The Diffusion LLM generation process starts with noise and iteratively refines the output using a transformer model that can modify multiple tokens in parallel. This allows parallelization of output token generation, allowing faster output speeds because many output tokens are generated at the same time. Key takeaways: ➤ Amongst comparable size/price-class models, Mercury 2 performs competitively in intelligence vs. output speed. While it does not have leading intelligence, it’s output speed is more than 3X the next fastest model in this class (benchmarks based on first party endpoints or the median of providers serving the model where a first party endpoint is not available) ➤ Key strengths include agentic coding & terminal use and instruction following. Mercury 2 performs at similar level to Claude 4.5 Haiku on Terminal-Bench Hard and scores 70% on IFBench (Instruction Following), outperforming gpt-oss-120B, GPT-5.1 Codex mini, and GPT-5 nano Inception Labs background: This is the second release from Inception Labs. The founders were previously professors from Stanford, UCLA, and Cornell and have contributed to AI research & technologies including Flash Attention, Decision Transformers, and Direct Preference Optimization (DPO). See below for further analysis.