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    1. Home
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    3. Inspect Evals
    Inspect Evals icon

    Inspect Evals

    Security Testing

    A library of LLM and AI agent evaluations built on the Inspect AI framework, with a searchable catalogue and a register for external evals.

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    At a Glance

    Pricing
    Open Source

    Inspect Evals is a library of evaluations for Inspect AI, released under the MIT License and free to use, copy, modify and distribute. Model provider API costs are external.

    Engagement

    Available On

    macOS
    Linux
    Web
    API
    VS Code

    Resources

    WebsiteDocsGitHubllms.txt

    Topics

    Security TestingLLM EvaluationsAI Development Libraries

    Alternatives

    ToolathlonSWE-benchLLM Stats
    Developer
    UK AI Security InstituteCentral London, United KingdomEst. 2023

    Listed Oct 2026

    About Inspect Evals

    Inspect Evals is a library of evaluations built using Inspect AI. It is maintained by Generality Labs, a London-based nonprofit, and was founded in 2024 with contributions from the UK AI Security Institute, Arcadia Impact, and the Vector Institute. The documentation site catalogues 184 evaluations, of which 129 live in the repository and 55 are external listings.

    What It Is

    Inspect Evals is a collection of ready-to-run benchmarks and safety evaluations for language models and AI agents. Each evaluation is an Inspect AI task that you run against a model from your chosen provider. Coverage in the catalogue spans several areas: coding, math and reasoning, cybersecurity and capture-the-flag challenges, agent safety and prompt injection, alignment and deception, bias, biology and chemistry knowledge, and multimodal understanding.

    How It Works

    You install the package from PyPI with pip install inspect-evals, or sync a checked-out repository with uv sync. You then run tasks with the Inspect CLI, for example inspect eval inspect_evals/arc_easy --model openai/gpt-5-nano, or run several together with inspect eval-set. Tasks can also be imported as Python objects and run from code. Logs from runs can be examined with inspect view. Inspect supports many model providers, including OpenAI, Anthropic, Google, Mistral, AWS Bedrock, Hugging Face, vLLM, and Ollama.

    Register and Contribution

    The Inspect Evals Register lets authors add a listing that points to their own implementation and documentation. The register is where the external evaluations in the catalogue come from. The repository currently accepts pull requests only from pre-approved contributors, and issues should be raised with .eval logs that demonstrate the problem.

    Setup Notes

    Python 3.11 or 3.12 is recommended. The README suggests at least 35 GB of free disk space, and about 100 GB for evals that pull Docker images. Most evals need around 0.5 GB of RAM, but some Docker-based evals need up to 32 GB. Cache location can be changed with the INSPECT_EVALS_CACHE_DIR variable.

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    Pricing

    OPEN SOURCE

    Open Source (MIT)

    Inspect Evals is a library of evaluations for Inspect AI, released under the MIT License and free to use, copy, modify and distribute. Model provider API costs are external.

    • MIT License
    • Install via pip install inspect-evals
    • Library of evaluations built using Inspect AI
    • Run from standalone repository or as a dependency

    Capabilities

    Key Features

    • Catalogue of 184 evaluations searchable and sortable on the docs site
    • Benchmarks for coding, math, reasoning, cybersecurity, agent safety, alignment, bias, and science
    • Run evals via Inspect CLI, eval-set, or Python API
    • Inspect Evals Register for listing external evaluations
    • Guides for task configurability, comparing results over time, and running specific eval versions
    • Configurable dataset cache location
    • Log viewing with inspect view

    Integrations

    Inspect AI
    OpenAI
    Anthropic
    Google
    Mistral
    Azure AI
    AWS Bedrock
    Together AI
    Groq
    Hugging Face
    vLLM
    Ollama
    Docker
    VS Code
    Inspect Harbor
    API Available
    View Docs

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    Developer

    UK AI Security Institute

    The UK AI Security Institute (AISI) builds tools and conducts research to evaluate the safety and security of frontier AI systems. AISI developed Inspect AI in collaboration with Meridian Labs as an open-source framework for rigorous LLM evaluations. The institute operates under the UK Government's Department for Science, Innovation and Technology and publishes its evaluation tooling publicly under permissive open-source licenses.

    Founded 2023
    Central London, United Kingdom
    100 employees

    Used by

    UK government departments and national-…
    Google DeepMind
    OpenAI
    Anthropic
    +2 more
    Read more about UK AI Security Institute
    WebsiteGitHub
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