GEPA vs Promptimal
GEPA
gepa-ai.github.ioPromptimal
github.comSide by side
| Figure | GEPA | Promptimal |
|---|---|---|
| Price from | Free | — |
| Free plan | Yes | — |
| Free trial | — | — |
| Open source | — | — |
| Linux | — | Yes |
| API | Yes | — |
| Self-hosted | Yes | — |
| Plans published | 1 | 0 |
| Spec score · AI Prompt Generators | 8.6 (#4) | 6.9 (#23) |
| Installation | The project’s documented install command is `pip install gepa`. | The README gives `pipx install promptimal` as the installation command. |
| License | The GitHub repository lists the project under the MIT license. | The GitHub repository identifies the project as MIT licensed. |
| What it does | GEPA is an LLM-based text evolution engine for optimizing prompts, code, configurations, agent architectures, policies, and other text-representable artifacts. | Promptimal is a command-line tool that iteratively improves AI prompts using a genetic algorithm, without requiring a dataset. |
Plans
In their own words
GEPA
GEPA is a free, open-source Python package for optimizing prompts, code, configurations, agent architectures, policies, and other text-based artifacts. Its optimize_anything API connects to any system through an evaluator you write, so DSPy or another framework is not required. GEPA examines execution traces and evaluator feedback, uses language-model reflection to diagnose problems and propose targeted mutations, then selects candidates with Pareto-aware criteria. It can optimize API-only GPT, Claude, and Gemini models without model-weight access. Human-readable traces explain changes and support agent debugging. Built-in adapters cover Default, Confidence, DSPy Full Program, Generic RAG, MCP, TerminalBench, AnyMaths, and LangChain, with integrations including MLflow, Comet ML Opik, Pydantic AI, and cookbook projects. You can limit metric calls and set several stopping conditions. GEPA works through API or self-hosted deployment, installs with pip, and uses the MIT license.