Mercury 3 challenges GPT-6 Luna: 40 times larger than its predecessor, official speed tests show it processes over 1,000 tokens per second.
1 hours ago
Beating AI News – U.S. AI firm Inception has launched its diffusion language model, Mercury 3. Unlike standard large language models (LLMs) that generate tokens one by one, Mercury 3 produces batches of text in parallel and iteratively refines them. Inception notes the new model has over 40 times more parameters than the original Mercury, yet still delivers 1,068 tokens per second on NVIDIA GPUs, nearly matching the 1,107 tokens per second of its predecessor, Mercury 2.5. Its context window has been expanded from 260,000 to 1 million tokens. In published self-tests, Mercury 3’s overall performance at medium inference settings is slightly higher than GPT-6 Luna and Claude Haiku 5.5, with generation speeds 4 to 8 times faster than both. On the DeepSWE coding benchmark, Mercury 3 scores 46.3%, lagging behind Haiku 5.5’s 51.6%; however, it leads with 51.1% on SWE-Bench Atlas, versus the rival’s 32.3%. Inception’s co-founder acknowledged on Hacker News that the new model cannot yet replace Opus or Fable as a primary agent, but can already handle subtasks like code writing. Mercury 3 is now accessible via Inception API, OpenRouter, Baseten, and Vercel. During the launch period, it is priced at 50% off: $0.10 per million input tokens and $0.35 per million output tokens, compared to regular rates of $0.20 and $0.70 respectively. The company is offering 100 million free tokens for trial use. However, the token speed advertised by Inception may not be attainable for regular users. OpenRouter data shows Mercury 3’s median output speed is approximately 180 tokens per second, just one-sixth of the official benchmark speed.
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