Inception: Mercury Coder
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Mercury Coder is a code-specialized diffusion language model from Inception Labs, built on the same parallel token refinement architecture as Mercury. It is available in Mini and Small sizes.
On fill-in-the-middle tasks, Mercury Coder Small scored 84.8% average accuracy, exceeding Codestral 2501 (82.5%). On MultiPL-E, it reaches 82.0% in C++, 83.9% in JavaScript, and 82.6% in TypeScript. In Copilot Arena human evaluations, Mercury Coder Mini ranked second in user preference with an average latency of just 25 milliseconds.
It is the go-to choice for real-time code completion, autocomplete, and apply-edit workflows where both speed and accuracy are critical.
Context Window 128K
tokens
Max Output 32K
tokens
Input Cost $0.25
per million tokens
Output Cost $0.75
per million tokens
Release Date Mar 31, 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 Coder is no longer available through Puter.js. Explore other AI models for alternatives.
| Price per 1M tokens | |
|---|---|
| Input | $0.25 |
| Output | $0.75 |
Mercury Coder was created by Inception and released on Mar 31, 2025.
Mercury Coder supports a context window of 128K tokens. For reference, that is roughly equivalent to 256 pages of text.
Mercury Coder can generate up to 32K tokens in a single response.
Yes — the Mercury Coder 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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