Arize Phoenix vs Promptfoo
Arize Phoenix
arize.comPromptfoo
promptfoo.devSide by side
| Figure | Arize Phoenix | Promptfoo |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | Yes |
| Web | Yes | Yes |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 3 |
| Spec score · Llm Developer Tools | 8.2 (#7) | 8.3 (#6) |
| Spec score · AI LLM Evaluation Tools | 8.1 (#14) | 8.4 (#13) |
| Spec score · Prompt Engineering Tools | 8.1 (#12) | 8.5 (#10) |
| Spec score · LLM Observability Tools | 8.1 (#16) | 8.3 (#13) |
| Deployment | Phoenix can run locally or be self-hosted using Docker, Kubernetes, or a cloud environment. | The Community plan can run locally or be self-hosted, while Enterprise includes managed cloud deployment and On-Premise supports deployment on the customer’s infrastructure. |
| Evaluations | Teams can score traces and spans with LLM-based evaluators, code checks, or human labels. | Promptfoo evaluates prompts across multiple models and opens a web view for comparing outputs. |
| Integrations | Documented integrations include frameworks and providers such as LlamaIndex, LangChain, DSPy, OpenAI, Bedrock, and Anthropic. | Documented integrations include LangChain, LangGraph, CrewAI, MCP, Splunk, Burp Suite, GitHub Actions, GitLab, Jenkins, CircleCI, Azure Pipelines, and Bitbucket Pipelines. |
| License | The Phoenix page describes the project as ELv2 licensed. | The open-source project is distributed under the MIT license. |
| Support | The Phoenix documentation points users to a Slack community for questions and developer discussion. | Community support is provided through chat and GitHub issues, while Enterprise includes professional services and dedicated Slack support. |
Plans
In their own words
Arize Phoenix
Arize Phoenix is free, open-source software for tracing, evaluating, debugging, and improving AI applications. It captures model calls, retrieval, tool use, and custom logic as OpenTelemetry traces. Teams can score traces and spans with LLM evaluators, code checks, or human labels. Prompt tools provide versioning, side-by-side testing, and call replay, while dataset experiments compare evaluation results across application versions. Documented integrations include LlamaIndex, LangChain, DSPy, OpenAI, Bedrock, and Anthropic, plus evaluation libraries such as Harbor, Ragas, Cleanlab, and MLflow. Phoenix runs locally or can be self-hosted with Docker, Kubernetes, or a cloud environment; Arize says self-hosting keeps traces in the user’s environment. Self-hosted authentication supports OAuth2 identity providers with an OpenID Connect well-known endpoint. The Phoenix plan costs nothing and leaves trace spans, ingestion, projects, and retention under user management. The project is ELv2 licensed and built by Arize AI and the open-source community.
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.