Inception 发布扩散式推理模型 Mercury 2
Introducing Mercury 2 – Inception
Inception 发布 Mercury 2,称其为全球最快的推理语言模型,采用扩散式并行精炼而非自回归逐 token 解码,生成速度提升超过 5 倍。官方数据为 NVIDIA Blackwell GPU 上 1,009 tokens/sec,定价 $0.25/1M 输入 token、$0.75/1M 输出 token,支持可调推理、128K 上下文、原生工具调用和 schema 对齐的 JSON 输出,并兼容 OpenAI API。该模型面向编码补全、智能体循环、实时语音和搜索 RAG 等延迟敏感场景,现已可用。
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官方给出扩散式推理的生成机制与速度、价格、上下文等参数,读者可据此判断它在延迟敏感场景的适用性。
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The fastest reasoning LLM, powered by diffusion
Today, we're introducing Mercury 2 — the world's fastest reasoning language model, built to make production AI feel instant.
Why speed matters more now
Production AI isn't one prompt and one answer anymore. It's loops: agents, retrieval pipelines, and extraction jobs running in the background at volume. In loops, latency doesn’t show up once. It compounds across every step, every user, every retry.
Yet current LLMs still share the same bottleneck: autoregressive, sequential decoding. One token at a time, left to right.
A new foundation: Diffusion for real-time reasoning
Mercury 2 doesn't decode sequentially. It generates responses through parallel refinement, producing multiple tokens simultaneously and converging over a small number of steps. Less typewriter, more editor revising a full draft at once. The result: >5x faster generation with a fundamentally different speed curve.
That speed advantage also changes the reasoning trade-off. Today, higher intelligence means more test-time compute — longer chains, more samples, more retries — bought at the direct expense of latency and cost. Diffusion-based reasoning gets you reasoning-grade quality inside real-time latency budgets.
Mercury 2 at a glance
Mercury 2 shifts the quality-speed curve for production deployments:
Speed: 1,009 tokens/sec on NVIDIA Blackwell GPUs; Price: $0.25/1M input tokens · $0.75/1M output tokens; Quality: competitive with leading speed-optimized models; Features: tunable reasoning · 128K context · native tool use · schema-aligned JSON output
We optimize for speed users actually feel: responsiveness in the moments users experience - p95 latency under high concurrency, consistent turn-to-turn behavior, and stable throughput when systems get busy.
“Inception’s Mercury 2 demonstrates what’s possible when new model architecture meets NVIDIA AI infrastructure. Surpassing 1,000 tokens per second on NVIDIA GPUs underscores the performance, scalability, and versatility of our platform to power the full spectrum of AI workloads.”
What Mercury 2 unlocks in production
Mercury 2 excels in latency-sensitive applications where the user experience is non-negotiable.
1. Coding and editing
Autocomplete, next-edit suggestions, refactors, interactive code agents - workflows where the developer is in the loop and any pause breaks flow.
“Suggestions land fast enough to feel like part of your own thinking, not something you have to wait for.”
Max Brunsfeld, Co-Founder, Zed
2. Agentic loops
Agentic workflows chain dozens of inference calls per task. Cutting latency per call doesn't just save time, it changes how many steps you can afford to run, and how good the final output gets.
“We’re now leveraging the latest Mercury model to intelligently optimize campaign execution at scale. By surfacing insights and dynamically enhancing delivery in real time, we’re driving stronger performance, greater efficiency, and a more resilient, AI-powered advertising ecosystem. This advancement reinforces our commitment to autonomous advertising, where intelligent systems continuously refine execution to deliver measurable outcomes for our clients.”
“We’ve been evaluating Mercury 2 because of its unparalleled latency and quality, especially valuable for real time transcript cleanup and interactive HCI applications. No other model has come close to the speed Mercury can provide!”
"Mercury 2 is at least twice as fast as GPT-5.2, which is a game changer for us."
3. Real-time voice and interaction
Voice interfaces have the tightest latency budget in AI. Mercury 2 makes reasoning-level quality viable within natural speech cadences.
“We build lifelike AI video avatars that hold real-time conversations with real people, so low latency isn't a nice-to-have, it's everything. Mercury 2 has been a big unlock in our voice stack: fast, consistent text generation that keeps the whole experience feeling natural and human.”
“Mercury 2 quality is excellent, and the model’s low latency enables more responsive voice agents.”
4. Search and RAG pipelines
Multi-hop retrieval, reranking, and summarization latencies stack fast. Mercury 2 lets you add reasoning to the search loop without blowing your latency budget.
“Our partnership with Inception makes real-time AI for our search product practical. Every SearchBlox customer, across customer support, compliance, risk, analytics, and e-commerce, benefits from sub-second intelligence across all of their data.”
Mercury 2 is available now.
Mercury 2 is OpenAI API compatible. Drop into your existing stack - no rewrites required.
If you’re doing an enterprise evaluation, we’ll partner with you on workload fit, eval design, and performance validation under your expected serving constraints.
Mercury 2 is live. Welcome to diffusion.
Mercury 2 for Search: Fast enough to run a hundred times per query