Phoenix
Open-source tool for ML observability that runs in your notebook environment.
About Phoenix
Phoenix is an open-source tool designed for machine learning observability, providing a robust platform for evaluating, experimenting, and optimizing AI products in real time. As of 2026, Phoenix is a leading solution for developers working with large language models (LLMs), computer vision (CV), and tabular models, offering seamless integration and comprehensive monitoring capabilities. Built on top of OpenTelemetry, Phoenix ensures full transparency and flexibility, allowing users to start, scale, or transition without vendor lock-in. The tool's interactive prompt playground and streamlined evaluation processes enable developers to iterate on their LLM workflows efficiently, reducing time to production while enhancing model reliability. With over 2.5 million downloads monthly and a thriving community, Phoenix is trusted by top AI teams for its ability to visualize complex decision-making processes and identify performance bottlenecks. Its unique features, such as dataset clustering and visualization, make it an invaluable asset for debugging and fine-tuning AI applications. Whether you're a small startup or an enterprise, Phoenix offers tailored solutions to meet your needs, from free open-source options to comprehensive enterprise packages. By choosing Phoenix, developers gain access to a powerful toolset that not only enhances model observability but also fosters continuous improvement and innovation in AI development.
Phoenix Key Features
OpenTelemetry Integration
Phoenix leverages OpenTelemetry for seamless setup and comprehensive observability. This integration ensures full transparency and flexibility, allowing users to monitor AI models without vendor lock-in, making it easier to start, scale, or transition as needed.
Interactive Prompt Playground
The Interactive Prompt Playground provides a dynamic environment for testing and iterating on prompts. Users can compare different prompts, visualize outputs, and debug failures, all within their workflow, enhancing the efficiency of model development and fine-tuning.
Streamlined Evaluations and Annotations
Phoenix offers a robust evaluation library with pre-built templates that can be customized for any task. Users can incorporate human feedback to refine models, ensuring high-quality outputs and improving model performance over time.
Dataset Clustering & Visualization
This feature uses embeddings to identify semantically similar questions and document chunks, helping users isolate areas of poor performance. It aids in understanding model behavior and improving accuracy by visualizing data relationships.
Application Tracing
Phoenix provides total visibility into LLM applications through automatic or manual instrumentation. This feature allows users to collect detailed data on model operations, facilitating deeper insights and troubleshooting capabilities.
Open Source and Self-Hostable
As an open-source tool, Phoenix offers complete freedom from feature gates and restrictions. Users can self-host the platform, ensuring control over their data and customization to meet specific project needs.
LLM Workflow Iteration
Phoenix supports iterative development of LLM workflows, allowing developers to test models, leverage templates, and incorporate feedback seamlessly. This accelerates the deployment process and enhances model reliability.
Model Interpretability and Troubleshooting
Phoenix enhances model interpretability by visualizing complex decision-making processes. It flags potential issues such as hallucinations or poor generalizations, helping developers troubleshoot and refine models effectively.
Phoenix Pricing Plans (2026)
Free
- Unlimited users
- User-managed trace spans and retention
- Community support
- User-managed support
- Limited to self-hosting
AX Pro
- Unlimited users
- 50k trace spans per month
- 10 GB ingestion volume
- Email support
- Retention limited to 15 days
- Higher rate limits available in Enterprise
AX Enterprise
- Unlimited users
- Billions of trace spans
- 5 TB+ ingestion volume
- Dedicated support
- Custom pricing required
- Requires enterprise-level resources
Phoenix Pros
- + Open-source and self-hostable, offering full transparency and control.
- + Seamless integration with LLM, CV, and tabular models for comprehensive monitoring.
- + Interactive prompt playground enhances model iteration and debugging.
- + Streamlined evaluation processes with customizable templates and human feedback.
- + Robust dataset clustering and visualization tools for performance optimization.
- + Flexible pricing options cater to different user needs, from free to enterprise.
Phoenix Cons
- − May require technical expertise for initial setup and customization.
- − Self-hosting can be resource-intensive for smaller teams.
- − Limited to environments that support OpenTelemetry integration.
- − Advanced features may have a learning curve for new users.
- − Community support might not be as immediate as dedicated support.
Phoenix Use Cases
Real-Time Model Optimization
Data scientists use Phoenix to optimize AI models in real time, allowing for immediate adjustments and improvements based on live data. This results in more accurate and reliable AI products.
Enhanced Model Debugging
Developers utilize Phoenix to debug complex LLM workflows, identifying and resolving issues related to model performance and decision-making, leading to more robust AI applications.
Custom AI Development
Enterprises leverage Phoenix's customization capabilities to develop AI solutions tailored to specific business needs, enhancing operational efficiency and decision-making processes.
Educational Use in AI Training
Educational institutions incorporate Phoenix into AI training programs to provide students with hands-on experience in model development, evaluation, and optimization.
Integration with Existing Workflows
Teams integrate Phoenix into existing data science workflows to enhance model observability and performance, ensuring seamless operation and improved outcomes.
Human Feedback Incorporation
Organizations use Phoenix to incorporate human feedback into AI models, refining outputs and ensuring alignment with human expectations and ethical standards.
What Makes Phoenix Unique
Vendor-Agnostic Observability
Phoenix's use of OpenTelemetry ensures that users are not tied to any specific vendor, providing flexibility and freedom in model monitoring and optimization.
Comprehensive LLM Support
Phoenix offers extensive support for large language models, including tools for tracing, evaluating, and iterating on workflows, making it a versatile choice for LLM development.
Interactive and Customizable Tools
The platform's interactive playground and customizable templates allow users to tailor the tool to their specific needs, enhancing the development process.
Open Source and Self-Hostable
Being fully open source and self-hostable, Phoenix offers users complete control over their data and the ability to customize the platform without restrictions.
Who's Using Phoenix
Enterprise Teams
Enterprise teams use Phoenix to monitor and optimize large-scale AI deployments, ensuring models are performing as expected and delivering value to the business.
Freelancers
Freelancers leverage Phoenix for its open-source flexibility and comprehensive monitoring capabilities, allowing them to deliver high-quality AI solutions to clients.
Educational Institutions
Educational institutions use Phoenix as a teaching tool to provide students with practical experience in AI model development and observability.
AI Researchers
AI researchers utilize Phoenix to experiment with new model architectures and techniques, benefiting from its robust evaluation and debugging features.
Startups
Startups adopt Phoenix to quickly iterate on AI models, ensuring rapid development and deployment of innovative AI solutions.
How We Rate Phoenix
Phoenix vs Competitors
Phoenix vs TensorZero
TensorZero offers similar observability features but lacks the open-source flexibility of Phoenix. Phoenix's integration with OpenTelemetry provides greater transparency and control.
- + Open-source and self-hostable
- + Seamless OpenTelemetry integration
- + Comprehensive monitoring tools
- − TensorZero may offer more dedicated support options
- − Potentially easier setup for non-technical users
Phoenix Frequently Asked Questions (2026)
What is Phoenix?
Phoenix is an open-source tool for machine learning observability, designed to evaluate, experiment, and optimize AI products in real time. It integrates seamlessly with LLM, CV, and tabular models.
How much does Phoenix cost in 2026?
Phoenix offers a free open-source tier. The AX Pro plan is priced at $50 per month, while enterprise pricing is available on request.
Is Phoenix free?
Yes, Phoenix offers a free open-source tier that allows unlimited users and trace spans, with user-managed support and retention.
Is Phoenix worth it in 2026?
Phoenix is highly valuable for developers seeking comprehensive AI observability tools, offering flexibility, transparency, and robust features.
Best Phoenix alternatives in 2026?
Alternatives to Phoenix include TensorZero, Compass, Sourcely, AI Detector, and Haystack, each offering unique features and capabilities.
Phoenix vs competitors in 2026?
Phoenix stands out for its open-source nature, OpenTelemetry integration, and comprehensive monitoring tools, offering flexibility and transparency.
How to get started with Phoenix?
To start with Phoenix, users can download the open-source version from GitHub or sign up for a free trial of the cloud-based options.
What platforms does Phoenix support?
Phoenix supports integration with various LLM, CV, and tabular models, and is compatible with platforms that support OpenTelemetry.
Is Phoenix safe and secure?
Phoenix provides robust security measures, though users managing self-hosted deployments should implement additional safeguards.
Who should use Phoenix?
Phoenix is ideal for AI engineers, data scientists, tech startups, large enterprises, and educational institutions seeking AI observability tools.
What's new in Phoenix 2026?
Phoenix 2026 includes enhanced tracing capabilities, improved evaluation processes, and expanded integration options for LLMs.
How does Phoenix compare to alternatives?
Phoenix offers unique features such as OpenTelemetry integration and an interactive prompt playground, setting it apart from competitors.
Phoenix Search Interest
Search interest over past 12 months (Google Trends) • Updated 2/2/2026
Phoenix on Hacker News
VS Code Extension
Phoenix Company
Phoenix Quick Info
- Pricing
- Open Source
- Upvotes
- 214
- Added
- January 3, 2026
Phoenix Is Best For
- AI Engineers seeking robust observability tools
- Data Scientists focused on model optimization
- Tech Startups looking for scalable AI solutions
- Large Enterprises managing complex AI systems
- Educational Institutions teaching AI development
Phoenix Integrations
Phoenix Alternatives
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News & Press
Phoenix Motor's EdisonFuture Subsidiary Expands into Advanced Robotics with U.S. - Made Robotic Dog Platform - AI Insider
Gennie and Phoenix Television Partner On AI-Driven Conspiracy Docuseries Birds Aren’t Real - FormatBiz
Poll: Best Phoenix first dates - Axios
Paris Hilton Jokes That 'Mother is Mothering’ as She Struts in Chic Ballgown with Kids Phoenix, 3, and London, 2 - People.com
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