Inception: Mercury
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Mercury is the world's first commercial-scale diffusion large language model from Inception Labs. It generates text through iterative parallel refinement rather than sequential token prediction, enabling dramatically higher throughput without sacrificing output quality.
It matches the performance of frontier speed-optimized models such as GPT-4o Mini and Gemini 1.5 Flash across knowledge, coding, instruction-following, and math benchmarks, while running up to 10x faster. It is OpenAI API-compatible for straightforward integration.
Mercury is well-suited for API use cases that demand high concurrency, fast response times, or cost efficiency — including chat, summarization, and general-purpose text generation at scale.
Context Window 128K
tokens
Max Output 32K
tokens
Input Cost $0.25
per million tokens
Output Cost $0.75
per million tokens
Release Date Feb 24, 2025
Code Example
Add AI to your app with the Puter.js AI API, no API keys or setup required.
// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms").then(response => {
document.body.innerHTML = response.message.content;
});
<html>
<body>
<script src="https://js.puter.com/v2/"></script>
<script>
puter.ai.chat("Explain quantum computing in simple terms").then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
More AI Models From Inception
Mercury 2.5
Mercury 2.5 is a diffusion language model from Inception Labs. Unlike autoregressive models that emit one token at a time, it generates and refines tokens in parallel. Inception reports 1,107 tokens per second on standard GPUs, and says quality is comparable to cost-optimized models such as GPT-5.6 Luna (Low), Gemini 3.5 Flash-Lite, and Claude Haiku 4.5. Reported benchmark figures include 79% on GPQA Diamond and 77% on IFBench. Independent benchmark coverage was not published at release, so those numbers are Inception's own. Through the API it supports tunable reasoning, parallel tool calls, and schema-aligned JSON output. With a 260K context window and 65,536 max output tokens, it targets latency-sensitive work such as search and RAG pipelines that fire many calls per request, voice agents, and coding-assistant tasks like context compaction and routing.
ChatMercury 2
Mercury 2 is a diffusion-based reasoning language model from Inception Labs that refines all tokens in parallel rather than generating them sequentially, achieving over 1,000 tokens per second — roughly 5x faster than speed-optimized competitors like Claude Haiku and GPT-5 Mini at comparable quality. On reasoning benchmarks, Mercury 2 scores 91.1 on AIME 2025 and 73.6 on GPQA. It also placed second on the Copilot Arena leaderboard for quality while ranking first for speed overall. With a 128K context window, it is purpose-built for latency-sensitive applications — real-time assistants, high-throughput pipelines, and cost-conscious production workloads where reasoning capability matters.
Frequently Asked Questions
Mercury is no longer available through Puter.js. Explore other AI models for alternatives.
| Price per 1M tokens | |
|---|---|
| Input | $0.25 |
| Output | $0.75 |
Mercury was created by Inception and released on Feb 24, 2025.
Mercury supports a context window of 128K tokens. For reference, that is roughly equivalent to 256 pages of text.
Mercury can generate up to 32K tokens in a single response.
Yes — the Mercury API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.
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