{"slug": "mercury-3-launches-on-venice-bringing-parallel-token-generation-to-private-ai", "title": "Mercury 3 launches on Venice, bringing parallel token generation to private AI", "summary": "Inception Labs launched Mercury 3, a diffusion-based model that generates tokens in parallel, on October 19, 2026, and made it available through privacy-focused platform Venice.ai under pay-per-token pricing. Inception says Mercury 3 reaches 1,068 tokens per second on NVIDIA GPUs, carries a 1-million-token context window, and matches or beats OpenAI's GPT-6 Luna and Anthropic's Claude Haiku 5.5 on 8 to 9 of 12 internal benchmarks at 4 to 8 times their speed, though independent validation is still pending. The model is API-only with OpenAI compatibility under the model ID \"mercury-3\", priced at $0.20 per million input tokens and $0.70 per million output tokens, cut to $0.10 and $0.35 during a 50% launch discount.", "body_md": "# Mercury 3 launches on Venice, bringing parallel token generation to private AI\n\nInception Labs' diffusion-based model claims speeds above 1,000 tokens per second and is now accessible through the privacy-focused Venice platform\n\nMost chatbots write the way a nervous student fills in an exam: one word at a time, never looking back. Inception Labs is betting that approach is a bottleneck.\n\nThe company’s new model, **Mercury 3**, is now live on Venice.ai. It uses a diffusion architecture that generates and refines every token in a response at once, pushing output speeds past 1,000 tokens per second.\n\n## What Mercury 3 actually does\n\nInception Labs launched Mercury 3 on October 19, 2026. It is the fourth model in the company’s Mercury series.\n\nThe headline figure is speed. Inception says the model hits 1,068 tokens per second when running on [NVIDIA](https://cryptobriefing.com/markets/nvidia/) GPUs.\n\nMercury 3 drafts an entire response simultaneously, then sharpens all of it in parallel passes.\n\nSpeed is not the only spec. Mercury 3 ships with a 1-million-token context window, meaning it can hold a very large amount of text in working memory during a single task.\n\nIt also supports tool calling, structured outputs and tunable reasoning. Put simply, it can trigger external software, return answers in tidy machine-readable formats, and dial its thinking effort up or down.\n\n## Benchmarks, pricing and the fine print\n\nInception claims Mercury 3 outperforms or matches [OpenAI](https://cryptobriefing.com/markets/openai/)’s GPT-6 Luna and [Anthropic](https://cryptobriefing.com/markets/anthropic/)’s Claude Haiku 5.5 on 8 to 9 out of 12 benchmarks.\n\nAccording to Inception, the model shows particular strength in instruction following and agent-based coding. It reportedly does this while running at 4 to 8 times the speed of those rivals.\n\nThose benchmarks are internal, though. Independent validation is still pending.\n\n### AI, tech, and the markets they move—in one daily briefing.\n\nDaily. Free. Join 34,000+ readers across crypto, finance, and policy.\n\nInception also says Mercury 3 is more than 40 times larger in parameters than Mercury 1. Despite that growth, the company claims it keeps similar speed and efficiency.\n\nThere is one early real-world data point. An early partnering agent reportedly completed 50% of tasks on Mind2Web, a benchmark built around navigating websites to finish multi-step jobs.\n\nOn pricing, list rates are set at $0.20 per million input tokens and $0.70 per million output tokens. A 50% launch discount cuts that to $0.10 and $0.35 respectively.\n\nAccess is API-only, with compatibility for OpenAI’s systems. Developers can call it using the model ID “mercury-3”.\n\nOpenAI compatibility means teams already built around OpenAI’s tooling can, in theory, swap in Mercury 3 without rewriting their entire stack.\n\n## Why Venice is part of the story\n\nMercury 3 is being offered through privacy-focused platforms, including Venice.ai, under a pay-per-token model.\n\nThe integration landed shortly after launch.\n\n## How we got here\n\nThe Mercury line has been iterating quickly. Prior versions arrived across 2025 and 2026, with each release pushing the diffusion concept further.\n\n## What this means\n\nInception is targeting a specific slice of the market: low-latency work. That includes AI agents, real-time search, and voice and chat interactions.\n\nFor developers, the pitch is straightforward. Comparable quality to small frontier models, several times faster, at launch prices of $0.10 and $0.35 per million tokens.\n\nThe risk is in the verification. Self-reported benchmarks have a habit of looking better in the press release than in production, and the 8-to-9-out-of-12 claim has not yet been independently confirmed.\n\nThe discount is also temporary. Teams that build around the $0.10 and $0.35 rates should budget for the list prices of $0.20 and $0.70 once the promotion ends.\n\nThings to watch next: independent benchmark results, how Mercury 3 handles long tasks that actually use its 1-million-token window, and whether the agent performance seen on Mind2Web holds up beyond an early partner.\n\n**Disclosure:** This article was edited by Diego Almada Lopez. For more information on how we create and review content, see our\n\n[Editorial Policy](https://cryptobriefing.com/editorial-policy/).", "url": "https://wpnews.pro/news/mercury-3-launches-on-venice-bringing-parallel-token-generation-to-private-ai", "canonical_source": "https://cryptobriefing.com/mercury-3-launches-venice-diffusion-model/", "published_at": "2026-10-22 15:25:12+00:00", "updated_at": "2026-10-22 15:39:55.231181+00:00", "lang": "en", "topics": ["large-language-models", "ai-products", "ai-infrastructure", "ai-agents", "ai-tools"], "entities": ["Inception Labs", "Mercury 3", "Venice.ai", "NVIDIA", "OpenAI", "GPT-6 Luna", "Anthropic", "Claude Haiku 5.5"], "also_reported_by": [], "alternates": {"html": "https://wpnews.pro/news/mercury-3-launches-on-venice-bringing-parallel-token-generation-to-private-ai", "markdown": "https://wpnews.pro/news/mercury-3-launches-on-venice-bringing-parallel-token-generation-to-private-ai.md", "text": "https://wpnews.pro/news/mercury-3-launches-on-venice-bringing-parallel-token-generation-to-private-ai.txt", "jsonld": "https://wpnews.pro/news/mercury-3-launches-on-venice-bringing-parallel-token-generation-to-private-ai.jsonld"}}