Arize Phoenix vs Comet
Compare data AI Tools
22% Similar based on 2 shared tags
A
Arize Phoenix
Open source LLM tracing and evaluation that captures spans scores prompts and outputs, clusters failures and offers a hosted AX service with free and enterprise tiers.
Pricing Free, SaaS tiers by quote
Category data
Difficulty Beginner
Type Web App
Status Active
Comet
Experiment tracking evaluation and AI observability for ML teams, available as free cloud or self hosted OSS with enterprise options for secure collaboration.
Pricing Free / Contact sales
Category data
Difficulty Beginner
Type Web App
Status Active
Feature Tags Comparison
Only in Arize Phoenix
llmtracingopensourceotel
Shared
observabilityevaluation
Only in Comet
mlopsexperiment-trackinggovernance
Key Features
Arize Phoenix
- • Open source tracing and evaluation built on OpenTelemetry
- • Span capture for prompts tools model outputs and latencies
- • Clustering to reveal failure patterns across sessions
- • Built in evals for relevance hallucination and safety
- • Compare models prompts and guardrails with custom metrics
- • Self host or use hosted AX with expanded limits and support
Comet
- • One line logging: Add a few lines to notebooks or jobs to record metrics params and artifacts for side by side comparisons and reproducibility
- • Evals for LLM apps: Define datasets prompts and rubrics to score quality with human in the loop review and golden sets for regression checks
- • Observability after deploy: Track live metrics drift and failures then alert owners and roll back or retrain with evidence captured for audits
- • Governance and privacy: Use roles projects and private networking to meet policy while enabling collaboration across research and product
- • Open and flexible: Choose free cloud or self hosted OSS with APIs and SDKs that plug into common stacks without heavy migration
- • Dashboards for stakeholders: Build views that explain model choices risks and tradeoffs so leadership can approve promotions confidently
Use Cases
Arize Phoenix
- → Trace and debug RAG pipelines across tools and models
- → Cluster bad answers to identify data or prompt gaps
- → Score outputs for relevance faithfulness and safety
- → Run A B tests on prompts with offline or online traffic
- → Add governance with retention access control and SLAs
- → Share findings with engineering and product via notebooks
Comet
- → Hyperparameter sweeps: Compare runs and pick winners with clear charts and artifact diffs for reproducible results
- → Prompt and RAG evaluation: Score generations against references and human rubrics to improve assistant quality across releases
- → Model registry workflows: Track versions lineage and approvals so shipping teams know what passed checks and why
- → Drift detection: Monitor production data and performance so owners catch shifts and trigger retraining before user impact
- → Collaborative research: Share projects and notes so scientists and engineers align on goals and evidence during sprints
- → Compliance support: Maintain histories and approvals to satisfy audits and customer reviews with minimal manual work
Perfect For
Arize Phoenix
ml engineers data scientists and platform teams building LLM apps who need open source tracing evals and an optional hosted path as usage grows
Comet
ml engineers data scientists platform and research teams who want reproducible tracking evals and monitoring with free options and enterprise governance when needed
Capabilities
Arize Phoenix
Spans and Context Professional
Built in and Custom Intermediate
Clustering and Search Intermediate
Hosted AX Basic
Comet
Experiments and Artifacts Professional
Prompts and Rubrics Professional
Production Drift Professional
Roles and Private Networking Enterprise
Need more details? Visit the full tool pages: