Parallel Model Testing
Send a single prompt template to GPT-4, Claude 3, and Gemini simultaneously. Instantly compare raw JSON outputs, latency metrics, and exact token consumption side-by-side without managing multiple browser tabs.





















A local-first desktop client designed to test, grade, and benchmark prompts across major LLMs. Stop guessing how a model will perform and prove it against your datasets.
Send a single prompt template to GPT-4, Claude 3, and Gemini simultaneously. Instantly compare raw JSON outputs, latency metrics, and exact token consumption side-by-side without managing multiple browser tabs.
Your API keys and prompt history are stored in a local SQLite database. Nothing touches our servers.
Every iteration is automatically saved to your local database. Fork a prompt to test a new variable, track the exact changes that improved the output, and easily revert to past configurations.
Inject test data into your prompt templates to establish a baseline. When a new LLM drops, benchmark it against your historical data before trusting it in production.
Run your prompt against a full test dataset across multiple models at once. Review the batch outputs side-by-side and assign pass/fail grades to see exactly which model handles your edge cases.
Keep a clean history of your iterations. Fork a prompt to test a new variable, track the changes, and easily switch back to past versions.
Chat interfaces hide the details. Inspect raw API responses, latency stats, and exact token usage for every single request.
Run your prompt against a full test dataset across multiple models at once. Review the batch outputs side-by-side and assign pass/fail grades to see exactly which model handles your edge cases.
Keep your credentials on your machine. Your keys are encrypted via your OS keyring, saved to your local database, and sent strictly to the providers. We track nothing.
Bring your own keys. Connect OpenAI, Anthropic, Mistral, Gemini and XAI in seconds. Toggle models on/off to keep your workspace clean.
Adjust temperature, top_p, and frequency penalties to observe how different constraints impact your prompt results.
We chose Electron for cross-platform support, but kept the stack as simple as possible.
No heavy frameworks overhead. We built the interface using standard HTML, CSS, and vanilla JavaScript.
Your data lives in a standard SQLite file on your disk. Backup, version control, or delete it whenever you want.
{
"runtime": "Electron",
"security": "Context Isolated",
"frontend": "Vanilla JS + Web Components",
"database": "SQLite3 (Local-only)"
}
Batch-test your datasets and prove model reliability before hitting production.
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Learn about our permanent licensing and early-adopter pricing:
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