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Introducing Mercury Our General Chat Model

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Introducing Mercury, our General Chat Diffusion Large Language Model – Inception

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Introducing Mercury, our General Chat Diffusion Large Language Model

Sawyer Birnbaum

Chief of Staff

In February, we announced Mercury Coder , the first commercial-scale diffusion large language model (dLLM), which provides developers with ultra-fast code generation. Today, we’re excited to announce that Mercury, our first general chat model, is available to support a wider range of text generation applications. When benchmarked by Artificial Analysis, a leading third-party model evaluator, Mercury matches the performance of speed-optimized frontier models like GPT-4.1 Nano and Claude 3.5 Haiku while running over 7x faster.

Mercury GPT-4.1 Nano Claude 3.5 Haiku Gemini 2.5 Flash Qwen 3 32B Gemma 3 27B Mistral Small 3.1 Nova Lite

Throughput (tok/sec) 708 96 67 329 63 46 136 277

MMLU-Pro (% accuracy) 69 66 63 78 73 67 66 59

GPQA Diamond (% accuracy) 51 51 41 59 54 43 45 43

Humanity's Last Exam (% accuracy) 3.4 3.9 3.5 5.0 4.3 4.7 4.8 4.7

LiveCodeBench (% accuracy) 23 33 31 41 29 14 20 17

SciCode (% accuracy) 18 26 27 23 28 21 27 14

HumanEval (% accuracy) 85 88 86 89 90 89 86 84

MATH-500 (% accuracy) 83 85 72 93 87 88 71 77

AIME 2024 (% accuracy) 30 24 3 43 30 25 9.0 11

As such, Mercury is the next step towards a diffusion-based future for language modeling, replacing the current generation of autoregressive models with extremely fast and powerful dLLMs. Here are a few ways that early adopters are using Mercury. Real-Time Voice Mercury’s low latency enables it to power responsive voice applications, ranging from translation services to call center agents. The below plot shows the end-to-end latency of real-world voice agent prompts on Mercury compared with Llama 3.3 70B running on Cerebras. Although Mercury is running on standard NVIDIA GPUs, it provides significantly lower latency than Cerebras’s custom hardware. Interactive Online Websites Mercury is the founding LLM partner for Microsoft’s NLWeb project. Announced at the CEO keynote at Microsoft's Build Conference, NLWeb allows publishers to easily create natural language interfaces on their websites, providing a hallucination-free experience. When combined with Mercury, NLWeb’s architecture enables lightning-fast, natural conversations grounded in real data. Compared with other speed-focused models like GPT-4.1 Mini and Claude 3.5 Haiku, Mercury runs far faster, ensuring a fluid user experience. Read more about how Mercury is supporting NLWeb here . How to Use Mercury Explore our playground

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If you are an enterprise customer interested in Inception's dLLM technology, please reach out to us at sales@inceptionlabs.ai . Check out our tech report for more information about our dLLMs.

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May 12, 2026

Mercury 2 and the Rise of Real-time Subagents

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May 12, 2026

Mercury 2 and the Rise of Real-time Subagents

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Mar 30, 2026

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Mar 30, 2026

Introducing Mercury Edit 2

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Mar 24, 2026

Mercury 2 on PinchBench: Fast Diffusion Models and the Personal Agent Era

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Mar 24, 2026

Mercury 2 on PinchBench: Fast Diffusion Models and the Personal Agent Era

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·

May 12, 2026

Mercury 2 and the Rise of Real-time Subagents

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·

Mar 30, 2026

Introducing Mercury Edit 2

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Mar 24, 2026

Mercury 2 on PinchBench: Fast Diffusion Models and the Personal Agent Era

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Notability

notability 6.0/10

New general chat model release, no high traction indicated.