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Mentat Pricing & Plans 2026

Complete pricing guide for Mentat. Compare all plans, analyze costs, and find the perfect tier for your needs.

Try Mentat Free →Compare Plans ↓

Not sure if free is enough? See our Free vs Paid comparison →
Still deciding? Read our full verdict on whether Mentat is worth it →

🆓Free Tier Available
💎1 Paid Plans
⚡No Setup Fees

Choose Your Plan

Open Source

Free

mo

  • ✓Full Mentat CLI installation via pip
  • ✓Multi-file coordination capabilities
  • ✓MIT license with full source access
  • ✓Community support via GitHub
  • ✓Bring-your-own OpenAI API key
Start Free →

OpenAI API Usage

Pay-as-you-go (~$0.01–$5.00 per session)

mo

  • ✓GPT-4o: ~$2.50/$10 per 1M input/output tokens
  • ✓GPT-4 Turbo: ~$10/$30 per 1M input/output tokens
  • ✓128K+ context window support
  • ✓Typical refactoring session: $0.05–$1.00 with GPT-4o
  • ✓No subscription commitment — pay only for what you use
Start Free Trial →

Pricing sourced from Mentat · Last verified March 2026

Feature Comparison

FeaturesOpen SourceOpenAI API Usage
Full Mentat CLI installation via pip✓✓
Multi-file coordination capabilities✓✓
MIT license with full source access✓✓
Community support via GitHub✓✓
Bring-your-own OpenAI API key✓✓
GPT-4o: ~$2.50/$10 per 1M input/output tokens—✓
GPT-4 Turbo: ~$10/$30 per 1M input/output tokens—✓
128K+ context window support—✓
Typical refactoring session: $0.05–$1.00 with GPT-4o—✓
No subscription commitment — pay only for what you use—✓

Is Mentat Worth It?

✅ Why Choose Mentat

  • • Free and open-source (MIT license) with an active community on GitHub
  • • Coordinates complex multi-file changes automatically across entire projects
  • • Pay-per-use model via OpenAI API avoids fixed monthly subscription costs
  • • Command-line interface integrates seamlessly with existing terminal workflows and CI/CD pipelines
  • • Supports large context windows for broad codebase analysis
  • • No vendor lock-in - full code transparency allows security auditing and customization

⚠️ Consider This

  • • Requires OpenAI API access and associated costs
  • • Limited by LLM token context windows for large files
  • • May generate code that requires careful review
  • • Command-line interface may have learning curve for GUI-focused developers
  • • Dependent on external API availability and performance

What Users Say About Mentat

👍 What Users Love

  • ✓Free and open-source (MIT license) with an active community on GitHub
  • ✓Coordinates complex multi-file changes automatically across entire projects
  • ✓Pay-per-use model via OpenAI API avoids fixed monthly subscription costs
  • ✓Command-line interface integrates seamlessly with existing terminal workflows and CI/CD pipelines
  • ✓Supports large context windows for broad codebase analysis
  • ✓No vendor lock-in - full code transparency allows security auditing and customization

👎 Common Concerns

  • ⚠Requires OpenAI API access and associated costs
  • ⚠Limited by LLM token context windows for large files
  • ⚠May generate code that requires careful review
  • ⚠Command-line interface may have learning curve for GUI-focused developers
  • ⚠Dependent on external API availability and performance
  • ⚠May not understand highly domain-specific or proprietary patterns
  • ⚠Requires careful prompt engineering for complex tasks
  • ⚠No built-in code execution or testing capabilities

Pricing FAQ

How does Mentat differ from GitHub Copilot?

Mentat focuses on coordinated multi-file editing from the command line, while GitHub Copilot ($10/month) provides inline single-line and multi-line suggestions within IDEs like VS Code and JetBrains. Mentat understands entire project context and implements complex changes across multiple files simultaneously, whereas Copilot is optimized for real-time autocompletion as you type within a single file. Choose Mentat for large refactoring tasks; choose Copilot for day-to-day coding speed within an editor.

What are the costs associated with using Mentat?

Mentat itself is free and open-source under the MIT license, but it requires an OpenAI API key which charges based on token usage. As a rough guide, GPT-4o costs approximately $2.50 per million input tokens and $10 per million output tokens, while GPT-4 Turbo costs approximately $10/$30 per million tokens. A typical refactoring session processing 10,000–50,000 tokens of context might cost $0.05–$1.00 with GPT-4o. Larger sessions with full 128K context on GPT-4 Turbo could reach $2.00–$5.00. Refer to OpenAI's pricing page for the latest rates.

Can Mentat work with large codebases?

Mentat is limited by the LLM's token context window, so it works best when focused on specific files or directories rather than entire massive codebases at once. You can target specific areas using file path arguments, and Mentat respects .gitignore patterns to exclude irrelevant files. With GPT-4 Turbo's 128K token context window, you can process substantial portions of a project in a single session, but extremely large monorepos may need to be broken into focused segments for best results.

Is my code secure when using Mentat?

Mentat processes your code locally on your machine and only sends necessary context to OpenAI's API for processing during active sessions. As an open-source MIT-licensed project, the entire codebase is auditable on GitHub for security review, and no code is permanently stored on external servers beyond OpenAI's standard API data handling policies. You can review exactly what data is sent by examining the source code, and .gitignore patterns are respected to avoid sending sensitive files.

What programming languages does Mentat support?

Mentat supports any programming language that GPT-4 understands, which includes Python, JavaScript, TypeScript, Java, C#, Go, Rust, Ruby, PHP, Swift, Kotlin, C/C++, and dozens of others. It also handles configuration files (YAML, JSON, TOML), markup languages (HTML, Markdown), shell scripts, and SQL. Performance is generally strongest for languages well-represented in the model's training data, particularly Python, JavaScript, and TypeScript, with diminishing returns for less common or newer languages.

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More about Mentat

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