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prompt-optimizer

by linshenkx 32.2k stars NOASSERTIONAI & LLM Tools
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About prompt-optimizer

Prompt Optimizer is a tool designed to improve AI-generated responses by optimizing input prompts. It supports various AI models and offers multiple deployment options including web, desktop, and browser extensions.

The tool helps users refine prompts through iterative improvements, enabling better accuracy and quality in AI outputs. It includes features for testing, evaluating, and comparing different prompt versions to determine their effectiveness.

Key features

  • Intelligent optimization with multi-round iterative improvements
  • Dual mode optimization for system and user prompts
  • Analysis and compare evaluation for prompt effectiveness
  • Integration with multiple AI models including OpenAI and Gemini
  • Image generation capabilities including text-to-image and image-to-image
  • Multi-platform support as web, desktop, and Chrome extension
  • Secure architecture with client-side data processing
  • Advanced testing mode with context variables and multi-turn conversations

Download v2.11.7

Jun 23, 2026
View all 10 versions

Frequently asked questions

Is prompt-optimizer free?
Yes. prompt-optimizer is free and open-source software, distributed under the NOASSERTION license.
Which platforms does prompt-optimizer support?
prompt-optimizer provides downloads for Windows, macOS, Linux.
What is the latest version of prompt-optimizer?
The latest version is v2.11.7, released on Jun 23, 2026.
What is Prompt Optimizer?
Prompt Optimizer is a tool that helps improve AI-generated responses by optimizing the input prompts used with various AI models.
How can I use Prompt Optimizer?
It can be used via a web application, desktop application, Chrome extension, or Docker deployment. An online version is also available for immediate use.
What AI models does Prompt Optimizer support?
It supports mainstream AI models including OpenAI, Gemini, DeepSeek, Grok, and others.
Is there a license for Prompt Optimizer?
Yes, it is licensed under AGPL-3.0.

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