LiveBench vs Promptfoo
LiveBench
livebench.aiPromptfoo
promptfoo.devSide by side
| Figure | LiveBench | Promptfoo |
|---|---|---|
| Price from | — | Free |
| Free plan | — | Yes |
| Free trial | — | — |
| Open source | — | Yes |
| Web | Yes | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | — | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 0 | 3 |
| Spec score · LLM Evaluation Tools | 7.2 (#22) | 8.4 (#6) |
| Product | LiveBench is described as a challenging, contamination-free LLM benchmark. | Promptfoo helps developers and enterprises build secure, reliable AI applications. |
| Support | The repository invites model evaluation requests by GitHub issue or email at [email protected]. | Community support is provided through chat and GitHub issues, while Enterprise includes professional services and dedicated Slack support. |
Plans
In their own words
LiveBench
LiveBench is an open-source benchmark for evaluating large language models, designed to limit test-set contamination and use objective scoring. Its current scope is 23 tasks across Reasoning, Coding, Agentic Coding, Mathematics, Data Analysis, Language, and Instruction Following, with a refresh every six months. The leaderboard presents overall and category scores, and model rows expand to show subtasks. Insight views cover quality versus cost, ranked cost, and category profiles; cost per successful task is calculated as (Σ cost ÷ Σ questions ÷ score) × 100 for the selected scope. Questions have verifiable ground-truth answers and can be scored automatically without an LLM judge. The public project provides benchmark code and links to data on Hugging Face, as well as a Python command-line evaluation pipeline. It supports OpenAI-compatible endpoints and implemented inference for Anthropic, Cohere, Mistral, Together, and Google models. Local inference is unmaintained. Agentic coding evaluations require Docker, and task images may take up to 150 GB to store.
Promptfoo
Promptfoo helps developers and enterprises evaluate prompts and test AI applications for security risks. It compares prompt outputs across multiple models in a web view. Red-team testing simulates users to look for prompt injections, jailbreaks, data leaks, business rule violations and insecure agent tool use. Its getting-started guide lists more than 60 providers, including OpenAI, Anthropic, Google and local models such as Ollama. Integrations include CI systems such as GitHub Actions, GitLab CI, Jenkins, Azure Pipelines, CircleCI and Bitbucket Pipelines, plus Splunk, Burp Suite, Google Sheets and MCP. Installation is available through npm, npx or Homebrew. Promptfoo requires Node.js 22.22.0 or newer and recommends Node.js 24 LTS. The free Community plan includes all LLM evaluation features and 10k red-team probes per month, and can run locally or be self-hosted. Enterprise includes managed cloud deployment; On-Premise runs on customer infrastructure. Promptfoo says it is based in San Francisco, is now part of OpenAI and remains open source.