Opik

Opik is Comet's open-source and hosted platform for AI observability and...

7.8/10 Useful

Active

Monthly OSS $0 Annual Free Cloud $0 Price Pro Cloud $19/month Price Enterprise custom

Best plan

Use Opik OSS or Free Cloud for early agent tracing and eval...

Risk: Opik buyers should model span volume, span retention...

Try Opik free

Editorial · no paid placements

Should you use it?

Opik is Comet's open-source and hosted platform for AI observability and evaluations. Pick it when agent traces, Test Suites, LLM-as-judge metrics, production monitoring, and annotation workflows need one home. Model span limits, retention, and additional-span costs before moving beyond the free routes.

Buy if Teams building agents that need trace and eval evidence
Pick Use Opik OSS or Free Cloud for early agent tracing and eval workflows. Move to Pro Cloud at $19/month when the team needs higher span volume or retention, then Enterprise for custom usage, deployments, SSO, compliance, and support
Skip if Teams that only need a local assertion runner

Plan guidance

What to buy

Best plan Use Opik OSS or Free Cloud for early agent tracing and eval workflows. Move to Pro Cloud at $19/month when the team needs higher span volume or retention, then Enterprise for custom usage, deployments, SSO, compliance, and support

Watch: Opik buyers should model span volume, span retention...

Price range OSS $0; Free Cloud $0; Pro Cloud $19/month; Enterprise custom

Upgrade only if Not for teams that only need a local assertion runner

Opik buyers should model span volume, span retention...

Current pricing source: Comet pricing

Fit

Use it for this, skip it for that

Best for

Teams building agents that need trace and eval evidence
Developers who want open-source observability with a hosted upgrade path
AI teams using Test Suites, assertions, datasets, and LLM-as-judge metrics
Teams that want Comet-hosted monitoring without buying a heavier platform first

Avoid if

Teams that only need a local assertion runner
Buyers that need an AI gateway or model-routing layer first
Teams unwilling to model span volume and retention
Non-technical buyers looking for a no-code workflow builder

Watch out: Opik buyers should model span volume, span retention, additional-span pricing, outside model spend, and whether Comet-hosted workflow value outweighs self-hosting or a broader LLMOps platform.

Recent changes

Only what affects the decision

Jun 28, 2026
Opik OSS
Self-hosted open-source route for the full AI observability and agent-testing feature set listed on pricing
Comet pricing
Jun 28, 2026
Free Cloud
Pricing page lists up to 10 team members, 25k spans/month, and 60-day retention
Comet pricing
Jun 28, 2026
Pro Cloud
Pricing page lists up to 50 team members, 100k spans/month, 60-day retention, and customizable span and retention limits
Comet pricing

Alternatives

Best swaps

Hugging Face

Open AI collaboration hub for models, datasets, Spaces, inference endpoints, evaluations, and enterprise ML workflows.

Free hub access; Pro $9/mo; Team $20/user/mo; Enterprise from $50/user/mo; paid compute/storage · 9.3/10 LiteLLM

Open-source LLM gateway and Python SDK for one OpenAI-compatible interface across 100+ model providers, with routing, virtual ke

Free MIT core outside enterprise directory; Enterprise custom · 8.8/10 promptfoo

Open-source LLM evaluation, red teaming, vulnerability scanning, guardrails, model security, MCP proxy, code scanning, and enter

Community free / Enterprise custom / On-Premise custom · 8.8/10

Build comparison

Proof and score math Verified Jun 28

Proof

Why this recommendation is trusted

Evidence Opik product page

Source: Registered source
Freshness: Current
Confidence: High confidence
Verified: Jun 28, 2026
Review: Jul 28, 2026
Volatility: Volatile

High-volatility evidence needs frequent review.

Editorial score

Unweighted average of 4 axes · confidence high

Utility 8/10

How much real work it can do for a competent operator, end to end.
Value 8/10

What you get for the dollar relative to the closest alternative.
Moat 7/10

How hard it would be for a competitor to replicate the underlying advantage.
Longevity 8/10

How likely the product is to still be best-in-class 24 months out.

Verified facts

Best For AI product and agent teams that need traces, production monitoring, automated eval workflows, LLM-as-judge metrics, Test Suites, assertions, annotation, and agent playground workflows.
high Drifts 2026-06-28 Opik product page
Pricing Anchor Comet's pricing page lists Opik OSS at $0, Free Cloud at $0 with up to 10 team members and 25k spans/month, Pro Cloud at $19/month with up to 50 team members and 100k spans/month, and Enterprise as custom.
high Volatile 2026-06-28 Comet pricing
Watch Out For Opik buyers should model span volume, span retention, additional-span pricing, outside model spend, and whether Comet-hosted workflow value outweighs self-hosting or a broader LLMOps platform.
high Volatile 2026-06-28 Comet pricing
Tracing Scope Opik tracing docs cover full execution paths, production root-cause debugging, cost and latency tracking, multi-turn conversations, feedback scores, and integrations with AI frameworks and coding agents.
high Drifts 2026-06-28 Opik tracing docs
Evaluation Scope Opik evaluation docs cover datasets, Test Suites, metrics, custom metrics, experiment tracking, annotation queues, and production evaluation workflows.
high Drifts 2026-06-28 Opik evaluation docs

Full review notes Long-form details, FAQ, and source history

Opik is Comet’s AI observability and evaluation platform for agentic applications. It is available as open-source software and as hosted Opik Cloud.

The buyer reason to care is evidence around agent behavior. Opik logs agent steps, traces tool calls, supports Test Suites and assertions, runs LLM-as-judge metrics, and helps teams monitor quality, cost, and latency in production.

System Verdict

Pick Opik when agent traces and evals need one operating surface. It is strongest for teams that want Test Suites, assertions, datasets, LLM-as-judge metrics, production monitoring, annotation, and agent debugging in one workflow.

Skip it when the first need is routing or broad workflow automation. LiteLLM, Portkey, or Respan fit better for gateway control. n8n or Dify fit better for workflow/app building.

Best plan guidance: start with Opik OSS or Free Cloud. Move to Pro Cloud at $19/month when span volume, team size, or retention exceeds the free route.

Key Facts


Core job	AI observability and evaluations for agents
Deployment	Open-source self-hosting or hosted Cloud
License	Apache-2.0
Free hosted tier	Free Cloud, up to 10 team members and 25k spans/month
First paid tier	Pro Cloud at $19/month
Main caveat	Span volume and retention decide real hosted cost

When To Pick Opik

You need agent traces. Opik is built for following each step an agent takes, including retrieval, tool calls, and user interactions.
You want evals close to production. Test Suites, assertions, datasets, and production monitoring make it easier to catch regressions.
You need LLM-as-judge workflows. Built-in and custom metrics help teams evaluate outputs at scale.
You want an OSS plus cloud path. Teams can self-host or start on hosted Free Cloud before buying Pro Cloud.
You need coding-agent observability. Opik docs describe integrations for AI frameworks and coding-agent workflows.

When To Pick Something Else

OpenTelemetry-first observability: OpenLIT or Traceloop when telemetry standards are the primary buyer criterion.
Prompt and dataset operations: Langfuse, LangSmith, or Braintrust when prompt release management and dataset workflows are already the center of gravity.
Security and red-team evals: promptfoo when jailbreaks, MCP exposure, and model-security testing are the main concern.
Code-first eval frameworks: DeepEval or Ragas when tests need to live in CI or notebooks first.
Gateway control: LiteLLM or Portkey when routing, budgets, keys, and caching matter more than eval UI.

Pricing

Opik was checked on June 28, 2026 against Comet’s product, pricing, docs, repository, and license sources.

Plan	Public price	Buyer fit
Opik OSS	$0	Self-hosting the open-source feature set
Free Cloud	$0	Early team use, up to 10 team members, 25k spans/month, 60-day retention
Pro Cloud	$19/month	Up to 50 team members, 100k spans/month, 60-day retention, and customizable usage
Enterprise	Custom	Custom usage, flexible deployments, SSO, compliance, support, and procurement controls
Additional spans	$5 per 100k spans	Needed when agent workflows generate more traces than included
Additional retention	$29 per 100k spans	Needed when historical trace evidence must last longer

The practical buying advice: Opik is compelling if the team has real agent runs to inspect. If the product is still at notebook stage, start free and prove which traces, tests, and metrics would actually gate releases.

Failure Modes

Span meters can grow fast. Multi-agent workflows can emit many spans for one user request.
Eval metrics can drift. LLM-as-judge metrics need calibration and periodic human review.
OSS still needs operations. Self-hosting shifts uptime, storage, upgrades, backups, and access control to the team.
It is not a gateway. Opik observes and evaluates; it does not replace model routing, caching, fallback, or key policy.
Hosted retention matters. Free and Pro both list 60-day retention in the checked pricing surface, so long-lived audits may need extra spend or Enterprise terms.

Change History

2026-06-28: Added Opik after verifying Comet product, pricing, docs, repository status, and Apache-2.0 license.

Methodology

This page was produced by the aipedia.wiki editorial pipeline. Scoring follows the four-dimension rubric at /about/scoring/ (Utility x Value x Moat x Longevity, unweighted average). Last verified 2026-06-28 against Comet product, pricing, docs, repository, and license sources.

FAQ

Is Opik free? Yes. Opik has an OSS route at $0 and a Free Cloud tier at $0. Pro Cloud is listed at $19/month, and Enterprise is custom.

What is Opik best for? Opik is best for teams building AI agents that need trace debugging, production monitoring, Test Suites, assertions, datasets, LLM-as-judge metrics, and annotation workflows.

Opik vs OpenLIT? Opik is stronger when hosted agent eval workflows and Comet’s Test Suites matter. OpenLIT is stronger when OpenTelemetry-native self-hosted observability is the primary requirement.

Sources

Opik product page: product positioning and agent observability scope
Comet pricing: OSS, Free Cloud, Pro Cloud, Enterprise, span, and retention pricing
Opik docs: documentation entry point
Opik tracing docs: tracing, production debugging, cost, latency, and integrations
Opik evaluation docs: Test Suites, metrics, experiments, and annotation queues
Opik GitHub repository: repository status
Opik license: Apache-2.0 license

Category: AI Infrastructure · AI Coding · AI Automation
Alternatives: OpenLIT · Langfuse · LangSmith · Braintrust

Share LinkedIn

Was this review helpful?

Embed this score on your site Free. Links back.

HTML

<a href="https://aipedia.wiki/tools/opik/" target="_blank" rel="noopener"><img src="https://aipedia.wiki/badges/opik.svg" alt="Opik on aipedia.wiki" width="260" height="72" /></a>

Markdown

[![Opik on aipedia.wiki](https://aipedia.wiki/badges/opik.svg)](https://aipedia.wiki/tools/opik/)

Badge value auto-updates if the editorial score changes. Attribution via the link is required.

Cite this page For journalists, researchers, and bloggers

News writers

According to aipedia.wiki Editorial at aipedia.wiki (https://aipedia.wiki/tools/opik/)

APA

aipedia.wiki Editorial. (2026). Opik: Editorial Review. aipedia.wiki. Retrieved July 2, 2026, from https://aipedia.wiki/tools/opik/

MLA 9

aipedia.wiki Editorial. "Opik: Editorial Review." aipedia.wiki, 2026, https://aipedia.wiki/tools/opik/. Accessed July 2, 2026.

Chicago

aipedia.wiki Editorial. 2026. "Opik: Editorial Review." aipedia.wiki. https://aipedia.wiki/tools/opik/.

BibTeX

@misc{opik-editorial-review-2026,
  author = {{aipedia.wiki Editorial}},
  title = {Opik: Editorial Review},
  year = {2026},
  publisher = {aipedia.wiki},
  url = {https://aipedia.wiki/tools/opik/},
  note = {Accessed: 2026-07-02}
}

Spotted an error or want to share your experience with Opik?

Every tool page is re-verified on a recurring cycle, and corrections land faster when readers flag them directly. If you spot a stale fact, a missing capability, or have used Opik and want to share what worked or didn't, the editorial desk reviews every message sent through this form.

Email editorial@aipedia.wiki

Report outdated info Help us keep this page accurate