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AI · February 3, 2025

Klarity – Open-source tool to analyze uncertainty/entropy in LLM output

We've open-sourced Klarity - a tool for analyzing uncertainty and decision-making in LLM token generation. It provides structured insights into how models choose tokens and where they show uncertainty. What Klarity does: - Real-time analysis of model uncertainty during generation - Dual analysis combining log probabilities and semantic understanding - Structured JSON output with actionable insights - Fully self-hostable with customizable analysis models The tool works by analyzing each step of text generation and returns a structured JSON: - uncertainty_points: array of {step, entropy,…

Klarity – Open-source tool to analyze uncertainty/entropy in LLM output launched on February 3, 2025 with 132 votes, #307 of 5,999 launches that month and more than 95% of that year's launches. The site was still online in September 2026, 1 year on.

Visit github.com ↗Alternativestop 5% of February 2025

In plain words

Klarity is an open-source tool that analyzes uncertainty in large language model token generation. It examines how models make decisions at each generation step, identifying points of high entropy and confidence. The tool provides structured JSON output combining log probability analysis with semantic understanding, helping developers understand where models show uncertainty. It is self-hostable with customizable analysis models and currently supports Hugging Face Transformers, tested with Qwen models.

written from the facts on this page · September 2026

From the sources

See Through Your Models. Contribute to klara-research/klarity development by creating an account on GitHub.

In the maker’s words, at launch

We've open-sourced Klarity - a tool for analyzing uncertainty and decision-making in LLM token generation. It provides structured insights into how models choose tokens and where they show uncertainty. What Klarity does: - Real-time analysis of model uncertainty during generation - Dual analysis combining log…

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