Mercury Edit
Ultra-fast AI code editing model that generates code at 1,000+ tokens per second.
Editorial take
Mercury Edit's standout capability is fastest code generation at 1000+ tokens/second. It is best suited for dev teams building custom coding tools or ides. A free plan is available, with paid plans starting at $0.25/1M tokens.
What is Mercury Edit?
Mercury Edit is a diffusion-based language model from Inception Labs built specifically for code editing. Unlike autoregressive models, it generates entire code blocks in parallel, achieving speeds of 1,000+ tokens per second - approximately 5x faster than comparable GPT-class models. This speed makes it well-suited for IDE autocomplete, fill-in-the-middle completions, and next-edit prediction.
It is OpenAI API-compatible, meaning it works as a drop-in replacement in any IDE or toolchain that supports the OpenAI format. Mercury Edit is available on AWS Bedrock and Azure AI Foundry, with 10 million complimentary tokens for new accounts.
Best for
Dev teams building custom coding tools or IDEs
Key strength
Fastest code generation at 1000+ tokens/second
Pros & Cons
π Pros
- β5x faster than comparable autoregressive models
- βOpenAI-compatible API - integrates directly with existing tools
- βAvailable on major cloud marketplaces (AWS, Azure)
π Cons
- βDeveloper API only - no consumer product
- β32K context window is smaller than many general-purpose LLMs
- βNo affiliate or reseller program
Key Features
- β Diffusion-based architecture (not autoregressive)
- β 1,000+ tokens/second generation speed
- β Fill-in-the-middle (FIM) autocomplete
- β Next-edit prediction using recent edit history
- β 32K context window
- β OpenAI API-compatible (drop-in replacement)
- β Available on AWS Bedrock and Azure AI Foundry
- β Structured output with schema constraints
Mercury Edit Pricing
β Mercury Edit has a free plan β no credit card required to start.
Pay-as-you-go
- β$0.75/1M output tokens
- β$0.025/1M cached input tokens
- β32K context window
- βPriority support
Mercury Edit vs Competitors
Developer resources
Related Tools
The AI assistant that actually reads the whole document and holds its ground
Ask Claude to summarize a 200-page report and it reads all 200 pages. That's not a figure of speech - its 200,000-token context window means you can paste an entire book, a year of emails, or a whole codebase and have a conversation about all of it at once. Most AI assistants quietly drop the earlier parts of long conversations. Claude doesn't. It's also unusually honest. Push back on a correct answer and Claude will explain why it's right rather than softening its position to keep you happy. That quality matters more than it sounds when you're using AI for research, analysis, or anything where you need accurate information more than agreeable information. For writing, Claude produces natural-sounding output with less formulaic phrasing and better paragraph rhythm than competitors. Anthropic built it with safety and honesty as design constraints, not afterthoughts, and it shows in day-to-day use.
AI assistant with text, images, voice, code, and web browsing in one tool
ChatGPT is the most widely used AI assistant, combining text, image generation, voice conversation, code execution, and web browsing. DALL-E 3 is built in for image generation. Advanced Voice Mode supports natural conversation. The code interpreter handles data analysis and visualization. Custom GPTs let you build or access specialized assistants for specific tasks - contract analysis, social media generation, tutoring, and thousands of others. ChatGPT covers the broadest range of capabilities compared to alternatives. The tradeoff: it's not always the strongest at any single task. Claude produces higher-quality writing. Perplexity returns better-cited research results. But if you need one tool that handles multiple types of work and connects to the widest third-party ecosystem, ChatGPT is the default choice.
The AI code editor that edits your whole codebase, not just the line you're on
Cursor is what happens when you build an editor around AI rather than adding AI to an editor. It's a VS Code fork, so your extensions and keybindings carry over, but the AI capabilities go significantly deeper than what Copilot can do as a plugin. The standout feature is multi-file editing. Describe what you want changed - "add authentication to all API routes" or "refactor this service to use the repository pattern" - and Cursor identifies every file that needs to change, shows you the diffs, and waits for your approval before applying anything. Getting six out of seven files right on a cross-cutting refactor is useful work that would take an hour manually. Codebase chat is the other one: ask "where does the user session get invalidated?" or "what does this function actually do?" and get accurate answers based on your actual code, not generic patterns. For joining a new codebase, this alone is worth the subscription price.
The AI coding assistant that works in your editor without asking you to change anything
Copilot's biggest advantage is not raw AI capability but distribution. It installs in VS Code, JetBrains, Vim, and most other editors you already use. You don't change your workflow at all - just get better autocomplete that suggests entire functions, not single lines. For teams with strict tool policies or organizations where not everyone will switch editors, this matters. Cursor may be technically stronger, but if half your team won't adopt it, Copilot's compatibility wins. Function-level completions have improved significantly and now work correctly more often than not. Context awareness across files is better. Copilot Chat has narrowed the gap with Cursor for specific questions. Limitations remain: you can't refactor across multiple files, and the chat feels added on rather than integrated into the core experience. At $10/month with a usable free tier, it's the natural first choice for developers new to AI-assisted coding.
This page contains affiliate links. We may earn a commission at no extra cost to you. Learn more.