Phoenix vs Weights & Biases

A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.

	Phoenix Evaluation	Weights & Biases Evaluation
Tagline	Open-source LLM and agent observability platform with tracing, evals, and experimentation built on OpenTelemetry.	The ML experiment tracker, now with LLM eval features.
Category	Evaluation	Evaluation
Pricing	Freemium· Open source (ELv2) + free Phoenix Cloud; paid Arize AX for enterprise	Freemium· Free personal; team from $50/mo per seat
Model	Multi-model	Platform (any LLM)
Editorial score	—	8.4 / 10
Use cases	llm-tracingagent-debuggingllm-evaluationprompt-experimentsrag-observability	ML experimentsLLM evalWeave
Pros	Genuinely open source (ELv2) with self-host parity, not a crippled OSS shell Native OpenTelemetry means no vendor lock-in for instrumentation Covers tracing, evals, annotation, and experiments in one tool Framework-agnostic: LangChain, LlamaIndex, DSPy, CrewAI, raw SDK calls all work	Industry-standard for ML tracking Weave adds LLM-native eval Mature, reliable Strong enterprise features
Cons	Self-hosting still requires you to manage storage, retention, and upgrades Eval UX is less polished than some managed competitors like LangSmith Free cloud tier is capped at two instances	Heavier UX than LLM-native tools LLM features still catching up
Website	phoenix.arize.com	wandb.ai

Pick Phoenix if

✅ Genuinely open source (ELv2) with self-host parity, not a crippled OSS shell
✅ Native OpenTelemetry means no vendor lock-in for instrumentation
✅ Covers tracing, evals, annotation, and experiments in one tool
✅ Framework-agnostic: LangChain, LlamaIndex, DSPy, CrewAI, raw SDK calls all work

Pick Weights & Biases if