Inception releases Mercury 3 diffusion language model
MarkTechPost: Inception Releases Mercury 3 Diffusion LLM at 1,068 Tokens per Second
Inception has released Mercury 3, the newest version of its diffusion language model. Mercury 3 is a diffusion LLM from Inception that writes answers in parallel, not token by token. Inception reports 1,068 tokens per second on NVIDIA GPUs and a 1M-token context window. On Inception’s own benchmark table, it leads GPT-6 Luna and Claude Haiku 5.5 on 8 of 12 tests. For developers building agents, voice bots and search tools, this is a speed-first model with competitive scores. TL;DR
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Inception has released Mercury 3, a diffusion language model that generates text by refining a full draft in parallel rather than writing one token at a time, achieving 1,068 tokens per second on NVIDIA GPUs with a 1 million token context window. Diffusion models potentially offer speed advantages over traditional autoregressive models by reducing sequential processing steps, and Mercury 3's performance suggests this approach scales effectively as models grow larger. In benchmark comparisons against competing models, Mercury 3 leads on 8 of 12 tests, with particularly strong results on instruction-following and coding tasks, though it underperforms on long-context retrieval and certain coding benchmarks. The model is available through API platforms at a launch price of $0.10 per million input tokens and $0.35 per million output tokens, primarily designed for developers building agents, voice bots, and search tools.
Explainer: Choosing Your Claude Model: Why Cheaper Isn't Always Faster for Agentic Workflows
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