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
- Real-time model performance monitoring for LLM, CV, and tabular models.
- Seamless integration with Jupyter notebooks for easy experimentation.
- Customizable dashboards for visualizing model metrics and insights.
- Automated alerts for model drift and performance degradation.
- Support for A/B testing to compare model variations 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
What Makes Phoenix Unique
OpenTelemetry Integration
Ensures seamless setup and full transparency, allowing users to manage their AI observability without vendor lock-in.
Interactive Prompt Playground
Enhances model iteration and debugging, offering a unique sandbox environment for prompt and model experimentation.
Comprehensive Monitoring Tools
Provides a suite of tools for tracking model performance and identifying bottlenecks, ensuring optimal AI application operation.
Self-Hosting Capabilities
Offers full control over deployments, allowing users to manage their own AI observability solutions without restrictions.
Human Feedback Integration
Allows for more accurate model assessments and improvements based on real-world interactions, setting it apart from competitors.
Who's Using Phoenix
AI Research Organizations
Use Phoenix to experiment with new AI models and techniques, enhancing research capabilities and fostering innovation.
Tech Startups
Startups leverage Phoenix to optimize their AI workflows, ensuring efficient model deployment and performance monitoring.
Large Enterprises
Enterprises use Phoenix for comprehensive AI observability, enabling them to manage complex AI systems and ensure optimal performance.
Data Science Teams
Data scientists utilize Phoenix to debug AI applications, improve model accuracy, and incorporate human feedback into evaluation processes.
Educational Institutions
Universities and colleges integrate Phoenix into their AI curricula, providing students with hands-on experience in model observability and optimization.
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 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
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