Lilac vs Weights & Biases
A side-by-side look at scores, pricing and features — with RECATOOLS' ASEAN-aware verdict for each.
Lilac
Archived open-source dataset curation tool, acquired by Databricks
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Weights & Biases
The near-default ML experiment tracker, now part of CoreWeave Forge
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| RECATOOLS Score | 6.5 / 10 | 8 / 10 |
| Capability | — | |
| Value for money | — | |
| Ease of use | — | |
| ASEAN readiness | — | |
| API quality | — | |
| Pricing | Open Source | Freemium |
| Free tier | Free: archived Apache-2.0 code on GitHub (databricks/lilac) and PyPI (0.3.9). The hosted Garden service and website are gone; nothing is for sale | Free: up to 5 model seats, 5 GB/mo storage, 1 GB/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 | 2023 | 2017 |
| Maker | Databricks (acquired 2024) | CoreWeave |
| Verdict | Lilac made large text datasets explorable: it clustered and auto-titled documents, ran semantic and keyword search, and flagged PII and near-duplicates through a local UI and Python API. Databricks acquired it in March 2... |
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 — and as of 30 September 2026 it lives inside CoreWea... |
| 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.