Inspect AI
Open-source LLM evaluation framework from the UK AI Security Institute with 200+ built-in benchmarks.
Pick Inspect AI if you're an AI safety researcher or ML engineer who needs a rigorous, auditable, self-hosted framework for benchmarking and red-teaming LLMs.
Skip it if you want a hosted, click-through eval dashboard or a lightweight prompt-testing tool for non-technical users.
Inspect AI is an open-source Python framework built by the UK AI Security Institute (AISI) and Meridian Labs for running rigorous evaluations of large language models. It ships with composable primitives — datasets, solvers, tools, scorers, and agents — plus a library of over 200 pre-built benchmark implementations covering coding, reasoning, multi-modal understanding, agentic tasks, and capture-the-flag security challenges.
What sets Inspect apart is its provenance and its focus on serious, reproducible model assessment rather than vibes-based leaderboards. It supports 20+ model providers (OpenAI, Anthropic, Google, HuggingFace, and more), a built-in ReAct agent with multi-agent primitives, and sandboxed tool execution via Docker, Kubernetes, or Modal for safely running untrusted model-generated code. It's aimed squarely at AI safety researchers, red teams, and model developers who need auditable eval pipelines.
The framework includes a web-based Inspect View for inspecting traces and a VS Code extension for authoring evals. Install with pip install inspect-ai; you bring your own model API keys and pay only the underlying provider costs. MCP tool support and external agent integration make it a credible backbone for building a full internal evals harness.
Inspect is quickly becoming the default serious-evals framework outside the big labs, and the AISI stewardship gives it credibility that most eval libraries lack. If you're building an internal model evaluation pipeline in 2026 and you're not paying for a hosted platform, this is the one to start with.
— The AI Tool Bible editorial team
Pros
- ✅ Backed by the UK AI Security Institute — serious pedigree for safety work
- ✅ 200+ pre-built evaluations ready to run out of the box
- ✅ Supports 20+ model providers plus sandboxed code execution
- ✅ Composable Python API with CLI, Inspect View UI, and VS Code extension
- ✅ Fully open source with no vendor lock-in
Cons
- ⚠️ Python-first — no low-code path for non-engineers
- ⚠️ Running large eval suites incurs real model API costs
- ⚠️ Steeper learning curve than hosted eval platforms
Use cases
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