OpenLIT vs W&B Weave
Both are observability & tracing tools. Here is how they actually differ on price, billing model and deployment.
OpenLIT
Apache-2.0 OpenTelemetry-native platform covering LLM tracing, evals, prompts, guardrails and a Vault - plus the one thing nearly every competitor ignores entirely, GPU monitoring for self-hosted inference.
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.
| OpenLIT | W&B Weave | |
|---|---|---|
| Category | Observability & Tracing | Observability & Tracing |
| Our rating | 4/5 | 4/5 |
| Starting price | $0 (Apache 2.0) | Per-seat plus usage |
| Billing meter | No usage metering | gb-ingested |
| Free plan | Yes | Yes |
| Free self-hosting | Yes, free | No or paid tier only |
| Best for | Teams running self-hosted inference on their own GPUs, where correlating GPU health with model performance matters. Also a strong free choice for anyone wanting broad AI engineering tooling in one Apache-2.0 package. | 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 OpenLIT
OpenLIT is the only tool in this category that takes the GPU layer seriously, and if you run your own inference that alone may decide it. Its OpenTelemetry GPU collector exports utilisation, memory, temperature and power as standard OTel signals, so you can correlate a latency regression with thermal throttling or a KV cache leak in the same dashboard - a class of problem that is completely invisible to Langfuse, LangSmith or Braintrust, because they assume you call an API. Beyond that it is unusually broad for a free tool - Apache 2.0 across the core, covering observability, evals, guardrails, prompt management, a Vault and a Playground. The trade-off is breadth over depth, since each module is lighter than a dedicated competitor, and the community is small at roughly 2,500 stars. Two things we could not resolve - an enterprise eBPF controller is referenced without clear licensing terms, and the project has recently described itself as a Harness Engineering platform without public explanation of what that means.
Full OpenLIT 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 OpenLIT and W&B Weave?
OpenLIT: Teams running self-hosted inference on their own GPUs, where correlating GPU health with model performance matters. Also a strong free choice for anyone wanting broad AI engineering tooling in one Apache-2.0 package. 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, OpenLIT or W&B Weave?
It depends entirely on your workload shape, because they meter differently - OpenLIT bills on no usage metering and W&B Weave bills on gb-ingested. Published starting prices are $0 (Apache 2.0) 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 OpenLIT or W&B Weave?
OpenLIT: Yes, free. 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.