GoKawiilInception launches Mercury 2.5, a faster diffusion language model at cutting price
Inception has released Mercury 2.5, an update to its diffusion-based language model that the company says is 40% more intelligent than Mercury 2 while keeping the same low-latency, low-cost performance. The model runs at over 1,100 tokens per second on standard NVIDIA GPUs, supports a 260K-token context window, and launches at an 80% discount, priced at $0.04 per million input tokens and $0.15 per million output tokens.
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Diffusion-based language models are a less common architecture than the autoregressive transformers used by most major AI labs, and Inception's claim that Mercury 2.5 is the largest such model ever trained signals growing confidence in this alternative approach. Its adoption across latency-sensitive uses like search, voice, and coding suggests diffusion models could carve out a niche where speed and cost matter more than raw benchmark scores.
- Mercury 2.5 offers a 40% intelligence boost over Mercury 2 while matching cost-optimized frontier models like GPT-5.6 Luna and Claude Haiku 4.5.
- It processes over 1,100 tokens per second on common NVIDIA GPUs and supports a 260K-token context window.
- Inception is offering an 80% launch discount, pricing input at $0.04 and output at $0.15 per million tokens.
Hands-On Large Language Models (O'Reilly book) — If a launch like Mercury 2.5 makes you want to understand what's actually happening under the hood of diffusion and transformer language models, this O'Reilly guide is a great place to start. It's a visual, code-along introduction to tokens, embeddings, and generation that pairs well with actually building on a fast, low-cost API.
See Hands-On Large Language Models (O'Reilly book) on Amazon → Affiliate link — we may earn a commission on purchases, at no extra cost to you. Product picked by AI based on this article; it is not a tested recommendation.Source: inceptionlabs.ai, 2026-09-08
Published there as: “Mercury 2.5”
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