Galileo vs W&B Weave
Both are observability & tracing tools. Here is how they actually differ on price, billing model and deployment.
Galileo
The best-funded evaluation-and-observability platform in this space, built around proprietary Luna eval models. Not to be confused with the Google-acquired text-to-UI tool of the same name. Real pricing is sales-led above $100/mo.
W&B Weave
Weights & Biases' LLM tracing and evaluation product, now owned by CoreWeave after a reported $1.7B acquisition. Billed on GB of trace data ingested rather than spans or requests, which is a genuinely different cost model to everything else in the category.
| Galileo | W&B Weave | |
|---|---|---|
| Category | Observability & Tracing | Observability & Tracing |
| Our rating | 4/5 | 4/5 |
| Starting price | $100/mo | Per-seat plus usage |
| Billing meter | span | gb-ingested |
| Free plan | Yes | Yes |
| Free self-hosting | No or paid tier only | No or paid tier only |
| Best for | Enterprise GenAI teams that have been burned by production hallucinations and want research-grade eval metrics plus guardrails, and can run a sales process | Teams already running Weights & Biases for model training and experiment tracking, who want LLM traces and evals in the same platform as their fine-tuning runs and are comfortable with usage-based ingestion billing. |
Our verdict on Galileo
Galileo is the best-funded and arguably most research-forward platform here, and the Luna eval models are a real bet on making evaluation cheap enough to run continuously. Two caveats. First, make sure you're evaluating this Galileo and not the design tool that shares the name - the pricing and reviews get conflated constantly. Second, above the $100 Pro tier everything is contact-sales, and self-host is Enterprise-only, so this is a platform you buy through a rep, not a card.
Full Galileo review →Our verdict on W&B Weave
W&B Weave is the strongest option in the category for one specific team - the one already on Weights & Biases. The lineage story is real and unmatched - a model fine-tuned in Sweeps and the eval run testing it appear in the same interface, which no AI-native competitor can offer because none of them do training. The instrumentation API is excellent, the custom scorers are plain Python, and the integration coverage is among the broadest available. Two things temper it. The billing metric is GB of trace data ingested, which is genuinely harder to forecast than per-span or per-seat pricing because it scales with prompt and context size, not just traffic. And CoreWeave now owns it following a reported $1.7B acquisition, which has come with interoperability pledges but leaves an open question about long-term direction. If you are not already a W&B customer, the bundled per-seat maths works against you and there are cheaper focused tools.
Full W&B Weave review →Frequently Asked Questions
What is the main difference between Galileo and W&B Weave?
Galileo: Enterprise GenAI teams that have been burned by production hallucinations and want research-grade eval metrics plus guardrails, and can run a sales process W&B Weave: Teams already running Weights & Biases for model training and experiment tracking, who want LLM traces and evals in the same platform as their fine-tuning runs and are comfortable with usage-based ingestion billing. Both sit in Observability & Tracing, so the decision usually comes down to billing model and deployment rather than raw capability.
Which is cheaper, Galileo or W&B Weave?
It depends entirely on your workload shape, because they meter differently - Galileo bills on span and W&B Weave bills on gb-ingested. Published starting prices are $100/mo and Per-seat plus usage respectively, but those numbers are not comparable until you apply them to the same traffic. Use our cost calculator to model both against your own request volume and span count.
Can I self-host Galileo or W&B Weave?
Galileo: No or paid tier only. W&B Weave: No or paid tier only. Free self-hosting means no licence fee, not no cost - you still own the infrastructure, upgrades and on-call.