Exgentic
Exgentic is an open-source leaderboard and evaluation framework for comparing general-purpose AI agents.
What Exgentic is
Exgentic is an open-source leaderboard and evaluation framework for comparing general-purpose AI agents. It provides a shared interface across benchmarks and domains including personal assistance, customer service, technical support, deep research, and software engineering. Listed benchmarks include τ²-bench, AppWorld, BrowseComp+, SWE-Bench, HotpotQA, GSM8K, and the Berkeley Function Calling Leaderboard. Listed agents include LiteLLM Tool Calling, SmolAgents, OpenAI MCP, Claude Code, Codex CLI, and Gemini CLI. Exgentic says it avoids prompt optimization and reports results from 100 sampled tasks per benchmark. Benchmark content and agent implementations are left unchanged, although interfaces may be adapted to a unified protocol. The repository contains the evaluation pipeline, implementations, configuration, and results for reproduction, with outcomes potentially varying by model version or nondeterministic output. Users can install a command-line tool or Python library, use OpenAI, Anthropic, or Hugging Face models, and run evaluations in Docker isolation. It is licensed under Apache License 2.0.
Good
- Open source under Apache License 2.0
- Consistent interface across many benchmarks
- Pipeline and results available for reproduction
- Supports OpenAI, Anthropic, and Hugging Face
- Docker runner provides container isolation
Watch out
- Results can vary with model versions
- Docker requires installation and a running daemon
- Evaluation sessions stop at 100 steps or actions
- Requires API credentials for some models
Who it suits
Exgentic suits agent builders, researchers, component developers, benchmark builders, and others comparing agent behavior. It is useful for users comfortable with command-line or Python-based evaluation.
Verdict
Exgentic offers a reproducible way to compare agents across varied tasks and benchmarks. Its technical setup and run limits make it most suitable for users who can manage code, credentials, and optional Docker isolation.
The facts
Each one read from Exgentic's own pages, with the date it was checked.
What it does
- Agents
- Listed agents include LiteLLM Tool Calling, SmolAgents, OpenAI MCP, Claude Code, Codex CLI, and Gemini CLI.checked 4 Oct 2026
- Available agents
- The listed agents include LiteLLM Tool Calling, HuggingFace SmolAgents, OpenAI MCP, Claude Code, Codex CLI, and Gemini CLI.checked 9 Oct 2026
- Available benchmarks
- The framework lists tau2, appworld, browsecompplus, swebench, hotpotqa, gsm8k, and bfcl benchmarks.checked 9 Oct 2026
- Benchmark handling
- Exgentic says it does not modify benchmarks or agent implementations, though it may adapt interfaces to its unified protocol.checked 4 Oct 2026
- Benchmarks
- The leaderboard covers personal assistance, customer service, technical support, deep research, and software engineering benchmarks.checked 9 Oct 2026
- Evaluation domains
- The leaderboard covers personal assistance, customer service, technical support, deep research, and software engineering tasks.checked 4 Oct 2026
- Evaluation framework
- Its framework provides a consistent interface for evaluating agents on benchmarks to compare performance and reproduce results.checked 4 Oct 2026
- Framework
- Exgentic provides a consistent interface for testing agents across benchmarks and domains to compare performance and reproduce results.checked 9 Oct 2026
- Installation
- The project documents installation as a command line tool with uv and use as a Python library with uv or pip.checked 4 Oct 2026
- Integrations
- The README documents API credentials for OpenAI and Anthropic models and support for Hugging Face models and Jobs.checked 9 Oct 2026
- Isolation
- The repository documents a Docker runner for full container isolation, requiring Docker to be installed and running.checked 4 Oct 2026
- License
- The framework is distributed under the Apache License 2.0.checked 9 Oct 2026
- License and support
- The repository states that Exgentic is licensed under Apache License 2.0 and directs support questions to GitHub issues.checked 4 Oct 2026
- Local use
- The README documents installation as a command-line tool or Python library and includes an evaluation dashboard command.checked 9 Oct 2026
- Methodology
- Exgentic says it avoids prompt optimization and reports results on 100 sampled tasks per benchmark.checked 4 Oct 2026
- Model integrations
- The quick start documents OpenAI and Anthropic API credentials, and the repository also describes support for Hugging Face models or evaluations on Hugging Face Jobs.checked 4 Oct 2026
- Open results
- The evaluation pipeline, agent implementations, configuration, and results are available for reproducing evaluations.checked 9 Oct 2026
- Product
- Exgentic is an open agent leaderboard that compares general purpose AI agents across diverse benchmarks.checked 4 Oct 2026
- Purpose
- Exgentic is an open agent leaderboard that evaluates general purpose AI agents across diverse domains.checked 9 Oct 2026
- Reproducibility
- The evaluation pipeline, agent implementations, and configuration are available in the repository; the project notes results may vary with model versions or nondeterministic outputs.checked 4 Oct 2026
- Run limits
- Evaluation sessions default to limits of 100 steps and 100 actions, and stop when either limit is reached.checked 9 Oct 2026
- Security and isolation
- The README documents a Docker runner for full container isolation when running evaluations.checked 9 Oct 2026
- Support
- The project directs users to open a GitHub issue for questions and support.checked 9 Oct 2026
Where it runs
- Evaluation approach
- Exgentic says it avoids prompt optimization and reports results on 100 sampled tasks per benchmark.checked 9 Oct 2026
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