instar-harness is an open-source framework (importable as 'instar') for benchmarking, measuring, and evaluating LLMs. It provides tools for systematic testing of model outputs, performance metrics, and intelligent routing between models. Currently a placeholder with the full release pending, it targets AI developers building reliable LLM-powered applications.
instar-harness sits in PulseGate's LLM eval & observability category. Accurately measuring and evaluating the performance of large language models and routing strategies. instar-harness is an open-source project aimed at developers. The project is open source (Apache-2.0). It runs on the command line, and it can be self-hosted.
Behind instar-harness is PurpleBlossomAI, and the product first shipped in 2026. The project is developed in the open on GitHub with 21 commits in the last 90 days. Among its 3 catalogued features are LLM evaluation, measurement harness, and model routing. instar-harness is currently in beta.
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