Weights & Biases vs Arize Phoenix
A side-by-side look at scores, pricing and features — with RECATOOLS' ASEAN-aware verdict for each.
Weights & Biases
The near-default MLOps platform, now with CoreWeave inference
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Arize Phoenix
Open-source LLM evaluation and observability
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| RECATOOLS Score | 8 / 10 | 7.8 / 10 |
| Capability | — | |
| Value for money | — | |
| Ease of use | — | |
| ASEAN readiness | — | |
| API quality | — | |
| Pricing | Freemium | Open Source |
| Free tier | Free 'Basics' tier: ~5 model seats, 5GB storage, 1GB/mo Weave ingestion | — |
| Paid from | Pro from $60/mo (teams <50); usage billed for storage/Weave/inference | — |
| Has API | ✓ | ✓ |
| Open source | ✗ | ✓ |
| Free to use | ✓ | ✓ |
| Users | 1,400+ organizations (incl. AstraZeneca, NVIDIA) | — |
| Founded | 2017 | 2023 |
| Maker | CoreWeave (acquired 2025) | — |
| Verdict | W&B is close to default infrastructure for ML teams — its experiment-tracking SDK is the sticky part, logging runs, metrics, and artifacts with a few lines of code. Weave extends that to LLM and agent observability w... |
Arize Phoenix is an open-source observability and evaluation toolkit for LLM and AI applications, offering tracing, prompt and RAG debugging, evals, and OpenTelemetry-based instrumentation that runs locally or self-hoste... |
| Full review → | Full review → |
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Comparisons cover up to 4 tools. Scores are RECATOOLS editorial assessments; verify current pricing on each vendor's site.