Arize Phoenix vs W&B Weave

Arize Phoenix is free, with no paid plan attached. W&B Weave is freemium — a usable free tier with paid plans above it. Both are listed under LLM Eval & Observability, so this is a like-for-like comparison. Neither is ranked above the other — Flocci carries no sponsored placement.

Arize Phoenix vs W&B Weave — straight answers

Arize Phoenix vs W&B Weave: what is the difference?

Arize Phoenix is free, with no paid plan attached and is listed for fully open-source, self-hostable with zero setup via `uvx` (pip/conda also supported). W&B Weave is freemium — a usable free tier with paid plans above it and is listed for agent-native tracing model with sessions, steps, tools and sub-agents as first-class concepts (not generic spans). Both sit in LLM Eval & Observability.

Is Arize Phoenix or W&B Weave cheaper to start with?

Arize Phoenix is the cheaper starting point: it is free, with no paid plan attached, while W&B Weave is freemium — a usable free tier with paid plans above it. Pricing tiers here come from the catalog, not from a promotional page.

Which should I choose, Arize Phoenix or W&B Weave?

Choose Arize Phoenix if you need fully open-source, self-hostable with zero setup via `uvx` (pip/conda also supported); choose W&B Weave if you need agent-native tracing model with sessions, steps, tools and sub-agents as first-class concepts (not generic spans). Flocci AI Tools does not rank one above the other — it shows both feature sets side by side and lets the requirement decide.

Arize Phoenix compared with W&B Weave: pricing tier, category, listed capabilities and links.
 Arize PhoenixW&B Weave
Pricing tierFreeFree tier + paid plans
Free to startYesYes
CategoryAI Models & Local ExecutionAI Models & Local Execution
TypeLLM Eval & ObservabilityLLM Eval & Observability
Listed capabilities
  • Fully open-source, self-hostable with zero setup via `uvx` (pip/conda also supported)
  • Combines tracing, evals, datasets, experiments and prompt playground in one local-first tool
  • AI engineering agent (PXI) built in for automated troubleshooting of traces
  • Agent-native tracing model with sessions, steps, tools and sub-agents as first-class concepts (not generic spans)
  • Pre-built safety/quality scorers for toxicity, bias, PII and hallucination detection out of the box
  • Built on Weights & Biases' existing ML-experiment infrastructure, useful for teams already on W&B
Tagsarize phoenix, llm observability open source, tracing, evaluation, rag debugging, freeweights and biases weave, agent observability, llm tracing, evaluation framework, free tier
Websitephoenix.arize.comwandb.ai
Full pageArize Phoenix details →W&B Weave details →
AlternativesArize Phoenix alternatives →W&B Weave alternatives →

Google Stax

LLM Eval & Observability
free
  • Build evals with human raters or LLM autoraters on your own data
  • Compare models and prompts on quality, latency and token cost
  • Prebuilt and custom evaluators

Laminar

LLM Eval & Observability
free
  • Open-source observability and evals platform for AI agents (Apache-2.0)
  • Traces, session replay for browser agents and evaluations
  • Self-hostable

DeepEval

LLM Eval & Observability
free
  • Open-source LLM evaluation framework with pytest-style tests and 50+ metrics
  • RAG, agent and conversational metrics; red-teaming module
  • Apache-2.0; optional Confident AI cloud has a free tier

EleutherAI LM Evaluation Harness

LLM Eval & Observability
free
  • Standard open framework for running hundreds of benchmarks (MMLU, GSM8K and more) against any LLM
  • Backs the Hugging Face Open LLM evaluations
  • MIT licensed CLI and Python library

OpenLLMetry (Traceloop)

LLM Eval & Observability
free
  • OpenTelemetry-based instrumentation for LLM calls, vector DBs and frameworks
  • Ships traces to Datadog, Grafana, Honeycomb or any OTel backend
  • Apache-2.0

Braintrust

LLM Eval & Observability
freemium
  • Free Starter plan ships model credits and scored evals with no card required
  • Unlimited users/projects/datasets/playgrounds even on the free tier
  • Built-in playground for side-by-side prompt/model comparison against production traces