Inception launches Mercury 3, a diffusion LLM it says runs at 1,068 tokens/s with a 1M-token context
Inception introduces Mercury 3, which it describes as the most capable diffusion-based LLM released to date. The company states it outperforms GPT-6 Luna and Claude Haiku 5.5 across a range of benchmarks while running 4-8x faster at over 1,000 tokens per second. It says Mercury 3 is more than 40x larger than Mercury 1. Early-access partners use it for voice and chat support, real-time tutoring, data engineering, and web navigation. The supplied text is truncated before the at-a-glance specifications, so the 1,068 tokens/s figure and 1M-token context in the title are not confirmed here.
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Inception introduces Mercury 3, which it describes as the most capable diffusion-based LLM released to date. The company states it outperforms GPT-6 Luna and Claude Haiku 5.5 across a range of benchmarks while running 4-8x faster at over 1,000 tokens per second. It says Mercury 3 is more than 40x larger than Mercury 1. Early-access partners use it for voice and chat support, real-time tutoring, data engineering, and web navigation. The supplied text is truncated before the at-a-glance specifications, so the 1,068 tokens/s figure and 1M-token context in the title are not confirmed here.
Key findings from the stored brief
- Inception claims Mercury 3 outperforms GPT-6 Luna and Claude Haiku 5.5 across a range of benchmarks.
- The company states Mercury 3 runs 4-8x faster, at 1,000+ tokens per second.
- Mercury 3 is described as more than 40x larger than Mercury 1.
- Early-access partners use it for voice and chat support, tutoring, data engineering, and web navigation.
Source claims not independently checked; the supplied text is truncated and omits the at-a-glance specifications cited in the title.
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Why this may matter
If the speed and quality claims hold, diffusion-based language models could offer a faster alternative to autoregressive models for latency-sensitive applications such as voice and real-time assistants.
Limits and open questions
Source claims not independently checked; the supplied text is truncated and omits the at-a-glance specifications cited in the title.
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