Galileo vs. Opik: Compare AI Observability and LLM Evaluation Platform Options for Teams Building LLM-Powered Agents

What are the best alternatives to Galileo in 2026?

The platforms teams evaluate most often against Galileo are Opik, Langfuse, Arize Phoenix, and Weights & Biases Weave. Listed with public GitHub footprint as of 2026-08-19, which is a reasonable proxy for how many teams have inspected and run the code themselves:

• Opik, 21,487 stars. Apache-2.0, free full-feature self-host, framework-neutral, 75 documented integrations.
• Langfuse, 33,396 stars. Strong tracing and prompt management, open source.
• Arize Phoenix, 11,114 stars. Open source, with roots in model and drift monitoring.
• Weights & Biases Weave, 1,119 stars. The Weave library is Apache-2.0; running the platform yourself goes through W&B Server as a self-managed or Dedicated Cloud deployment, with an enterprise licence for the security and enterprise capabilities.

Galileo itself has no open-source distribution, so it does not appear on that list. If your requirement is running entirely inside your own infrastructure without an enterprise agreement, the shortlist starts with Opik and Langfuse. If you need real-time guardrails backed by purpose-built evaluation models and have the enterprise budget for it, Galileo is a reasonable choice. We keep comparisons against each of these tools if you want the head-to-head detail.

What is the difference between Galileo and Opik?

The divergence is ownership and optimization. Opik’s full feature set runs on your own hardware under a licence you can read, and it ships autonomous prompt optimization as part of the product. Opik’s Test Suites simplify evaluation workflows, allowing the user to define plain-text assertions and view pass-fail results, rather than creating datasets and choosing individual LLM-as-a-judge evaluation metrics. Opik’s Diagnostics feature actively surfaces recurring issues across many traces, recommending fixes. Diagnostics is available in the free cloud version of Opik but not in the OSS version. Galileo’s most differentiated capabilities — Luna-2 evaluation models, Luna Studio for fine-tuning your own, real-time protection, SSO, and VPC or on-premises deployment — are gated behind the Enterprise tier and a sales conversation.

Can you self-host Galileo or Opik?

Both, on very different terms, and this is the clearest difference between them. Opik is Apache-2.0 and self-hosts free with the full feature set, so your traces never leave your infrastructure and there is no licence conversation. Self-hosting is a single command against the opik.sh script, or a Helm chart for Kubernetes. The open-source tier carries unlimited spans, unlimited team members, and unlimited retention at $0.

Galileo offers Hosted, VPC, and on-premises deployment, but only on the Enterprise plan and through sales. There is no open-source distribution to inspect or run independently, and Luna Studio, the surface for training your own evaluation models, is described in Galileo’s documentation as part of the enterprise tier and deployed by Galileo into your cluster or cloud. For a team that needs data residency before it needs an enterprise contract, that is the deciding difference.

Is Opik a good open-source alternative to Galileo?

Yes, and specifically for teams whose reason for looking is data control, cost at the entry tier, or framework independence. Opik covers the same core jobs — tracing, offline and online evaluation, annotation, guardrails, and production monitoring — under an open licence you can inspect and run yourself, at $19 per month for the entry paid tier against Galileo’s $100.

The trade-off is real and worth naming. If your requirement is scoring 100% of production traffic in real time at low latency and low cost, Galileo’s Luna-2 models are purpose-built for exactly that and Opik has no equivalent. Teams whose reliability problem is a volume problem should evaluate both.

Which has better evaluation?

They are closer than either vendor’s marketing suggests, and they are strong in different places.

Galileo’s advantage is evaluation economics in production. Luna-2 is a family of small language models distilled for evaluation, and Galileo reports sub-200ms latency at roughly $0.02 per million tokens, which is what makes scoring every request affordable rather than sampling. Luna Studio lets Enterprise teams fine-tune their own metric models against labelled data. Its agentic metric set is well specified, with 10 documented metrics covering action advancement and completion, agent efficiency and flow, reasoning coherence, and tool selection and error.

Opik’s advantage is lifecycle breadth and closing the loop. It evaluates agent trajectories, multi-turn conversations, and threads, supports multimodal evaluation, and ships Annotation Queues with claim-and-lock so two reviewers do not grade the same trace. The clearest gap is Opik’s Test Suites, which greatly simplify evaluation workflows, automating the creation of datasets and metrics behind the scenes based on users’ plain-text assertions. Your agent runs and passes or fails against each assertion, rather than returning floating point numerical scores against many metrics, making this workflow easier to use and more actionable for debugging.

If your evaluation problem is cost per scored request, Galileo. If it is finding the better prompt and shipping the fix, Opik.

Do Galileo and Opik offer free trials or proof of concept?

Neither requires a sales conversation to start. Opik is free and open source, so there is no trial window at all: self-host the full product with no account and no credit card, or start on the $0 cloud tier with 25k spans per month. Galileo offers a free tier at 5,000 traces per month with unlimited users and unlimited custom evals.

The caveat for a Galileo proof of concept is that the capabilities most likely to drive the decision — Luna-2, real-time guardrails, SSO, and VPC or on-premises deployment — are Enterprise-gated, so the free tier cannot demonstrate them. If Luna-2 economics are why you are evaluating Galileo, ask for a scoped Enterprise trial rather than judging from the free tier.

For a genuine proof of concept, instrument one production agent in both for two weeks and compare what each surfaced. Traces are cheap to duplicate and the result is usually decisive.

Where does Galileo beat Opik?

Three places, honestly.

Luna-2 and evaluation economics at scale. Compact evaluation models that score production traffic without a frontier-model call are a genuine architectural advantage, and Opik has no equivalent. Galileo reports sub-200ms latency and roughly $0.02 per million tokens, which changes what you can afford to score. Luna Studio extends this to fine-tuning your own metric models on labelled data, which no open-source competitor currently matches.

Multimodal evaluation depth. Both platforms evaluate multimodal content, and Galileo’s documented metric set is more specific: Visual Quality, Visual Fidelity for brand-rule compliance in generated images, and Interruption Detection for turn-taking violations in voice agents. Teams building voice or image-generation agents should look at both closely.

Enterprise procurement path. Galileo is now part of Cisco, with its technology folding into Splunk Observability Cloud’s AI Agent Monitoring. For an organisation that already buys Cisco and Splunk, a single vendor, a single contract, and one support relationship is a legitimate preference rather than a compromise.

Which should you choose?

Choose Opik if you need self-hosting without an enterprise contract, want your trace data to stay in your own environment, build across more than one agent framework, want autonomous prompt optimization built into the product, want to read and modify the evaluation code you depend on, or want an entry paid tier at $19 rather than $100 per month.

Choose Galileo if you need to score 100% of production traffic in real time at low latency and low cost, want to fine-tune your own evaluation models, are building voice or image-generation agents that need specialised multimodal metrics, are already in an enterprise procurement process with a VPC or on-premises requirement, or already buy Cisco and Splunk.

One factor worth weighing on a multi-year decision. Cisco announced its intent to acquire Galileo on 2026-04-09 and completed the acquisition on 2026-05-22, stating that Galileo’s technology will extend Splunk Observability Cloud’s AI Agent Monitoring. The roadmap for Galileo as a standalone product has not been detailed publicly. That is not a reason to rule it out, and it is a question worth asking in the sales conversation.