# Inception’s Mercury 3 Claims It Beats GPT-6 Luna and Claude Haiku 5.5 at Up to 8x the Speed URL: https://technosports.co.in/mercury-3-speed-benchmarks/ Published: 2026-10-24 Updated: 2026-10-24 Author: Raunak Saha **Quick take:** Inception, a startup that builds diffusion-based language models, has released Mercury 3. In its own benchmarks, the model beat OpenAI’s GPT-6 Luna and Anthropic’s Claude Haiku 5.5 on eight of 12 tests while running four to eight times faster. No outside group has published results yet, so treat the numbers as claims. ## A Different Way to Write Text Most chatbots write one token at a time, left to right. Mercury works differently. A [diffusion](https://en.wikipedia.org/wiki/Diffusion_model) language model drafts the whole answer at once, then refines every position in parallel over a few passes. That is the idea behind its speed. The question hanging over the approach has been whether it can scale, and Inception says Mercury 3 is its answer. ![Inception's Mercury 3 Claims It Beats GPT-6 Luna and Claude Haiku 5.5 at Up to 8x the Speed](https://images.technosports.co.in/2026/10/YO5OXn25zt3KJBJkUxO2kAwmS6o_converted-832x1024.avif) ## Mercury 3 vs GPT-6 Luna vs Claude Haiku 5.5 | Metric | Mercury 3 | Claude Haiku 5.5 | GPT-6 Luna | | --- | --- | --- | --- | | Speed (tokens per second, on Nvidia GPUs) | 1,068 | About 240 | About 130 | | Speed advantage | Baseline | About 4.5x slower | About 8x slower | | SWE-Bench Atlas (coding) | 51.1 | 32.3 | 33.3 | | DeepSWE (coding) | 46.3 | 51.6 | Not reported | | List price per million input tokens | $0.20 | $0.10 | $0.10 | | List price per million output tokens | $0.70 | $0.50 | $0.50 | | Launch price (input / output) | $0.10 / $0.35 | N/A | N/A | *Figures are from [SiliconANGLE’s report](https://siliconangle.com/2026/10/20/inception-says-mercury-3-beats-gpt-6-luna-and-claude-haiku-5-5-at-up-to-8x-the-speed/) and Inception’s own benchmarks. Speed ratios are our calculation from the tokens-per-second figures. Competitor prices are for typical prompts.* ## Where Mercury 3 Wins and Loses - **Wins:** Eight of 12 benchmarks. [Its biggest](https://technosports.co.in/avengers-doomsday-sets-six-years-later/) lead over GPT-6 Luna is in coding, on SWE-Bench Atlas. - **Loses:** It trails Haiku 5.5 on DeepSWE, a second coding test, and on one long-context test. - **Close calls:** GPT-6 Luna won two benchmarks, each by less than a point. ![Inception's Mercury 3 Claims It Beats GPT-6 Luna and Claude Haiku 5.5 at Up to 8x the Speed](https://images.technosports.co.in/2026/10/uA54aGA7yoIF8XSjD3KfiSp9efs_converted-1022x1024.avif) ## Key Specs | Detail | Information | | --- | --- | | Released | October 19, 2026 | | Context window | 1 million tokens (up from 260,000 in Mercury 2.5) | | Size | Not disclosed, but over 40 times larger than Mercury 1 | | Cached input | 90% cheaper than standard input | | Availability | Inception’s platform, OpenRouter, Baseten and Vercel | | Compatibility | Works with code written for OpenAI’s API with minor changes | Inception has also said Mercury 2 and Mercury 2.5 are no longer available to new users. ## Who Is Using It? Early customers care about delays that users can feel. Octen AI, a real-time search startup, says an answer taking five seconds feels broken on smart glasses, and reports a median generation time of 0.9 seconds in its tests. Tutoring app RevisionDojo says hints and marked answers now return in about a second. ![Inception's Mercury 3 Claims It Beats GPT-6 Luna and Claude Haiku 5.5 at Up to 8x the Speed](https://images.technosports.co.in/2026/10/cover-en-v2-1024x576.avif) ## The Business Behind It Inception was founded in 2024 by computer science professors Stefano Ermon, Aditya Grover and Volodymyr Kuleshov. Last November, it raised $50 million in a round led by [Menlo Ventures](https://en.wikipedia.org/wiki/Menlo_Ventures), with Microsoft’s M12 among the backers. Reuters reported in May that Microsoft was in talks to acquire it, with the startup seeking more than $1 billion, and that SpaceX had also approached it. No deal has been announced. ## What to Take Away | The Case For | The Case For Caution | | --- | --- | | Much faster output, useful for voice, search and agents | Benchmarks were run by Inception, not an independent lab | | 1 million token context window | Costs more per token than both rivals at list price | | Strong coding result on SWE-Bench Atlas | Loses on DeepSWE and one long-context test | If speed is your bottleneck, Mercury 3 deserves a test. If you care about price per token or consistent coding results, wait for independent benchmarks. Learn more about [large language models](https://en.wikipedia.org/wiki/Large_language_model), and see more AI coverage in our [technology section on TechnoSports](https://technosports.co.in/category/technology/), including our report on [Anthropic’s draft IPO filing](https://technosports.co.in/). *Sources: [SiliconANGLE](https://siliconangle.com/2026/10/20/inception-says-mercury-3-beats-gpt-6-luna-and-claude-haiku-5-5-at-up-to-8x-the-speed/), [Business Wire](https://www.businesswire.com/news/home/20261019090400/en/Inception-Launches-Mercury-3-Setting-a-New-Pareto-Frontier-in-Speed-and-Intelligence), [Inception](https://www.inceptionlabs.ai/blog/introducing-mercury-3), [Unite.AI](https://www.unite.ai/?p=489882).* ## Frequently Asked Questions What is Mercury 3? Inception’s flagship diffusion language model, released on October 19, 2026. How fast is it? Inception measured 1,068 tokens per second on Nvidia GPUs, versus about 240 for Claude Haiku 5.5 and about 130 for GPT-6 Luna. How much does it cost? List price is $0.20 per million input tokens and $0.70 per million output tokens, halved during the launch promotion. Has anyone verified the results? Not yet. No outside group has published its own results on Mercury 3.