Comet Opik is live · free plan, paid from $49/user/mo billed annually · last verified 21 Oct 2026 · viability healthy
Comet Opik
Open-source LLM observability, evaluation, and cost tracking for teams shipping agentic AI
If your team ships agents and the token bill keeps climbing, Opik treats cost tracking and regression testing as first-class rather than upsell. Agent Diagnostics, Test Suites, and the Ollie auto-fix assistant give it teeth beyond logging, and OpenTelemetry ingest now pulls traces from gateways like TrueFoundry and Nebius AI Cloud. Pick it for cost visibility and self-hosting; look at LangSmith instead if you need mature enterprise governance or a no-code UI.
Verdict generatedVerified 8d ago · liveness 80/100 · cite: rightaichoice.com/tools/comet-opik
- Engineering teams running agentic workflows in production
- ML engineers who need token-cost attribution per call
- Open-source projects wanting a self-hostable, inspectable stack
- Teams already on Comet ML extending into LLM observability
- Non-developers wanting a no-code observability UI
- Teams needing computer-vision or multi-modal evaluation
- Procurement-heavy enterprises requiring mature governance out of the box
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Skip Comet Opik if nobody on your team writes Python and you want a point-and-click eval dashboard — the entry points here are an SDK, an MCP server, and OpenTelemetry.
The free hosted tier caps at 3 users and 1 GB storage, so a team that adds a fourth engineer or outgrows a gigabyte has to move up or self-host
The free hosted tier (3 users, 1 GB) suits a solo engineer or a two-person prototype. Team at $49/user/mo billed annually is priced near closed peers like LangSmith, but you are paying for hosted convenience on software you could self-host for free under Apache 2.0. Enterprise is custom-quoted and adds self-hosting support and governance review.
In short
Comet Opik — Open-source LLM observability, evaluation, and cost tracking for teams shipping agentic AI. Best for Engineering teams running agentic workflows in production, ML engineers who need token-cost attribution per call, Open-source projects wanting a self-hostable, inspectable stack. Free to start; paid plans from $49/user/mo billed annually.
No head-to-head comparison for Comet Opik yet — the alternatives below are the closest matches we list.
What is Comet Opik?
Comet Opik — Open-source LLM observability, evaluation, and cost tracking for teams shipping agentic AI. Best for Engineering teams running agentic workflows in production, ML engineers who need token-cost attribution per call, Open-source projects wanting a self-hostable, inspectable stack. Free to start; paid plans from $49/user/mo billed annually.
Comet Opik is an Apache 2.0 framework for evaluating, testing, and monitoring LLM applications, built for engineering teams whose workloads have outgrown single-call debugging and now need to watch multi-step agents run in production. Opik logs LLM interactions, traces multi-step chains, and runs prompt A/B tests against evaluation metrics, so iteration rests on numbers rather than vibes. Because the source is open, you can read it, self-host it, and wire it into your own stack instead of renting a black box. The platform has moved past logging. Agent Diagnostics looks across a production run rather than at one trace, and Test Suites turn ad-hoc dataset and metric checks into repeatable regression tests. Agent Playground covers prototyping before a workflow ships, and Ollie, the auto-fix assistant, patches agent codebases when something breaks. Cost control is treated as a core feature. Advanced cost tracking surfaces token waste and recommends fixes, with Comet reporting Claude Code token-spend reductions of up to 30%. Opik now ingests TrueFoundry AI Gateway traces via OpenTelemetry, surfacing prompt, model and response for slow or costly calls, and it is listed in Nebius AI Cloud Applications. Comet also publishes research on how developers actually use coding agents, drawn from thousands of captured Claude Code sessions, and maintains an MCP server for terminal-based workflows. Against closed alternatives such as LangSmith, the pitch is transparency and cost visibility: you trade some enterprise governance and no-code polish for a stack you can inspect and self-host.
Key features
- Real-time LLM interaction logging and tracing for production apps
- Multi-step agent tracing across an entire run, not just one call
- Agent Diagnostics for cross-trace production agent analysis
- Test Suites for automated dataset and metric regression testing
- Agent Playground for early-stage agent prototyping
- Prompt A/B testing against evaluation metrics
- Evaluation metric dashboards for measuring output quality
- Ollie auto-fix assistant that patches broken agent codebases
- Advanced cost tracking that surfaces token waste and recommends fixes
- Claude Code token-spend reduction of up to 30%
- Prompt, model, and response surfaced for slow or costly calls from external gateways
- Native OpenTelemetry trace ingest from third-party AI gateways
- MCP server for terminal-based agent workflows
- Python SDK for instrumenting LLM applications
- CI/CD integration for turning evals into regression gates
Behind the verdict
Opik's defining advantage is that it is Apache 2.0. You can read every line, run it in your own VPC, and instrument with a Python SDK or OpenTelemetry without asking permission. For teams that have been burned by a closed observability vendor changing its pricing or sampling your prompts, that matters more than any feature grid. What separates it from a pure logger is the evaluation loop. Test Suites turn a dataset-plus-metric check into a regression test you can run in CI/CD, so a prompt change that breaks your agent gets caught before deploy. Agent Diagnostics widens the lens from one trace to a whole production run, which is the actual debugging unit for a multi-step agent. Prompt A/B testing against evaluation metrics closes the loop. Cost tooling is unusually concrete. Advanced cost tracking surfaces token waste and recommends fixes, Comet reports Claude Code token-spend cuts of up to 30%, and OpenTelemetry ingest from gateways like TrueFoundry surfaces the prompt, model and response behind every slow or expensive call. The Nebius AI Cloud listing extends that to Nebius users. Comet's own research — thousands of captured Claude Code sessions, plus terminal-UX work for the Opik MCP server — suggests the team is watching how agents are actually operated, not just theorized. Weaknesses are structural. Entry points are a Python SDK, an MCP server, and OpenTelemetry; there is no meaningful no-code path, so a product manager cannot self-serve a dashboard. Governance is thinner than closed competitors, which will frustrate procurement-heavy organizations. Multi-modal and computer-vision evaluation sit outside its scope. Hosted usage carries caps — the seed data records a free hosted tier at 3 users and 1 GB storage — and self-hosting removes the cap but adds operational burden. Cost tooling also stops at token spend rather than broader infrastructure cost. Where it fits: a small-to-mid engineering team running agentic workflows in production, already comfortable with Python and CI, that wants trace-level cost attribution and regression gates without a vendor lock-in conversation. Where it doesn't: a non-technical team wanting a point-and-click eval UI, or an enterprise that needs SSO, audit trails and governance sign-off on day one.
Models under the hood
as of 2026-10-23
Limitations
- Opik assumes a technical user base: the primary entry points are a Python SDK, an MCP server, and OpenTelemetry, with no meaningful no-code path for non-engineers.
- Advanced governance is still maturing relative to closed competitors, so procurement-heavy organizations may find it thin.
- Multi-modal and computer-vision evaluation are outside its scope.
- The free hosted tier caps at 3 users and 1 GB storage, which a growing team outgrows quickly; self-hosting under Apache 2.0 removes the storage cap but adds operational responsibility.
- Cost-optimization tooling focuses on token spend rather than broader infrastructure cost.
as of 2026-10-21
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Is Comet Opik still active?
Comet Opik is live · free plan, paid from $49/user/mo billed annually · last verified 21 Oct 2026 · viability healthy.
Viability score
How well maintained and how widely used is Comet Opik? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →What do users say about Comet Opik?
What people actually say about Comet Opik — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
ResearchedDiscussed by users across 2 sources (Hacker News, YouTube) · researched Aug 23, 2026.
Average across the 2 sources that answered — each source counts once, not each post.
- +Real-time logging and tracing with native OpenTelemetry support
- +Open-source (Apache 2.0) transparency avoids vendor lock-in
- +Advanced cost tracking could cut token spend up to 30%
- +Agent Playground speeds up early-stage agent prototyping
- +Test Suites turn ad-hoc evals into repeatable regression tests
- −No-code support is still lagging behind LangSmith
- −Enterprise features (governance, compliance) are catching up
- −Limited real-world community feedback outside vendor YouTube
- −Lacks rich media support like URL preview images in traces
- −Documentation and eval startup definition can be confusing
- • Self-hosting requires infrastructure and maintenance effort
- • Higher-tier plans may have setup or onboarding fees
How we verified this
Every listed fact about Comet Opik— pricing, features, links, status — is re-read from the vendor's own pages by our verification pipeline and each change is logged with a date; the last pass ran on 21 Oct 2026. Pages mix model-assisted synthesis with human review; see how we verify.
Verification history
We have re-verified Comet Opik 21 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — changed pricing page
- — changed setup time, pricing fit, features, switching out, pricing tiers, switching in, who should skip it, who it suits, our verdict, hidden costs, description, use cases
- — changed who it suits, summary, who should skip it, our verdict, features, description, pricing tiers
- — changed who should skip it, summary, description, pricing tiers, integrations, features, our verdict
- — changed who should skip it, description, our verdict, features, hidden costs, integrations, limitations, switching in, switching out, pricing fit, setup time, summary
- — changed who should skip it, pricing tiers, features, our verdict, description, who it suits
Showing the 6 most recent of 21 verification passes.
Free to cite with attribution — this page re-verifies continuously.
How much does Comet Opik cost in 2026?
Comet Opik: Free to start; paid plans from $49/user/mo billed annually. Pricing last verified 21 Oct 2026.
Plans compared
Every published Comet Opik tier, its price as the vendor publishes it, who it fits, and what it adds over the tier below. The 12-month cost projection follows.
| Plan | Price | Billing | Who it's for |
|---|---|---|---|
| Free | Free | — | A solo engineer or two-person prototype that wants hosted Opik tracing and prompt A/B testing without running infrastructureAdds: Starting tier: hosted Opik with a small user cap, Python SDK, eval dashboards and access to the Apache 2.0 source |
| Team | $49/user/mo billed annually | monthly, billed annually, per seat | A funded engineering team shipping agents to production that has outgrown 3 seats and 1 GB of hosted storageAdds: Adds more seats plus Agent Diagnostics across runs, Test Suites for regression testing, advanced cost tracking and OpenTelemetry ingest — $49/user/mo billed annually |
| Enterprise | Custom | quote | Organizations that need self-hosting support and a governance and deployment review before rolling Opik out widelyAdds: Custom contracting on top of Team, adding self-hosting support and a governance and deployment review with Comet |
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Where the pricing makes sense
The company stage and team size where Comet Opik's pricing actually pencils out — and where peers do it cheaper.
The free hosted tier (3 users, 1 GB) suits a solo engineer or a two-person prototype. Team at $49/user/mo billed annually is priced near closed peers like LangSmith, but you are paying for hosted convenience on software you could self-host for free under Apache 2.0. Enterprise is custom-quoted and adds self-hosting support and governance review.
Has Comet Opik's pricing changed?
No plan price for Comet Opik has moved since we began logging in Aug 2026; the pricing page is re-read on every verification pass.
Who should pick Comet Opik?
Pick Comet Opik if you are Engineering teams running agentic workflows in production, ML engineers who need token-cost attribution per call, Open-source projects wanting a self-hostable, inspectable stack, Teams already on Comet ML extending into LLM observability.
Look elsewhere if you are Non-developers wanting a no-code observability UI, Teams needing computer-vision or multi-modal evaluation, Procurement-heavy enterprises requiring mature governance out of the box, Teams wanting out-of-the-box content guardrails or safety filters.
Skip it if Skip Comet Opik if nobody on your team writes Python and you want a point-and-click eval dashboard — the entry points here are an SDK, an MCP server, and OpenTelemetry.
GeneratedReal-world workflow fit
Concrete scenarios for the personas Comet Opik actually fits — and what changes day-one when you adopt it.
Your support agent's token bill doubled last month and you can't tell which step is burning context. You point the Python SDK at Opik, then add OpenTelemetry ingest from your TrueFoundry gateway.
Outcome: Opik surfaces prompt, model and response for each slow or costly call, and Advanced cost tracking recommends where to trim, the same path Comet reports cutting Claude Code token spend by up to 30%.
A prompt tweak quietly regresses your agent's answer quality. You codify your dataset and metrics as a Test Suite and wire the eval run into CI/CD.
Outcome: A failing eval blocks the merge instead of reaching production, and prompt A/B tests show which variant actually scores better.
Security says no prompt data leaves the VPC. You deploy Opik self-hosted under Apache 2.0 and instrument with the Python SDK.
Outcome: Full tracing and evaluation run inside your own infrastructure, with no storage cap beyond what you provision yourself.
Use cases
- Trace and debug multi-step LLM chains in production
- A/B test prompts and compare outputs against evaluation metrics
- Build evaluation datasets that automatically score LLM responses
- Monitor latency and token usage across model versions
- Gate CI/CD pipelines on eval results to catch agent regressions
- Investigate a 400-turn agent session to see where it went wrong
- Prototype agents in the Agent Playground before shipping
- Self-host observability in your own VPC under Apache 2.0
Setup time & first value
How long it actually takes to get something useful out of Comet Opik — broken out by persona, not the marketing-page minute.
Python developer: an afternoon, since two lines of SDK instrumentation produce first traces. Platform engineer self-hosting: one to three days for deploy, OpenTelemetry wiring and storage. Non-technical stakeholder: no path — there is no no-code entry point.
Switching to or from Comet Opik
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From LangSmith: re-instrument via the Python SDK and re-upload datasets as Test Suites, then compare eval dashboards side by side before cutting over
- →From a logging-only stack (raw OpenTelemetry or app logs): point the OpenTelemetry exporter at Opik, including gateway traces from tools like TrueFoundry
- ↗To LangSmith: export traces and datasets, then re-instrument; you gain enterprise governance but lose self-hosting and Apache 2.0 transparency
Integrations
Tutorials & Learning
YouTube returned 6 videos for “Comet Opik”, and we withheld 5: 5 did not mention Comet Opik. Showing the 1 we can prove is about Comet Opik.
Official links
What are the best Comet Opik alternatives?
The closest alternatives to Comet Opik we list are LangSmith, Phoenix and LangWatch. Ranked by direct product-type match, not category overlap.
| Alternative | Pricing | Starts at | Last verified |
|---|---|---|---|
| LangSmith | Freemium | Pricing not published | — |
| Phoenix | Freemium | Pricing not published | — |
| LangWatch | Freemium | Pricing not published | — |
Alternatives to Comet Opik
View all
Tools that pair well with Comet Opik
Common stack mates teams adopt alongside Comet Opik, with the specific reason each pairing earns its keep.
LangSmith
LangSmith is agent and LLM observability from the LangChain team: trace, monitor, evaluate, and deploy AI agents.
Phoenix
Open-source LLM observability and agent evaluation you can trace, self-host, and eval end to end.
LangWatch
LangWatch is an open-source LLMOps platform for agent testing, LLM evaluation and OpenTelemetry-native LLM observability.
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