Comet Opik
Open-source LLM evaluation and observability for agentic systems with real-time tracing and cost optimization
Opik is a strong open-source choice for LLM evaluation and observability, especially with recent agent tracing, cost-tracking, and auto-fix features. However, its no-code capabilities are minimal and enterprise features lag behind LangSmith. Best for technical teams who want full control and transparency.
Verified 17d ago · liveness 95/100 · cite: rightaichoice.com/tools/comet-opik
- Developers evaluating LLM prompts with A/B testing and detailed metrics
- ML engineers monitoring LLM performance and cost in production
- Teams building LLM applications with complex agentic workflows
- Open-source projects needing transparent LLM testing and evaluation
- Teams needing advanced content guardrails or safety filters
- Non-developers seeking a no-code solution without coding
- Enterprises requiring multi-cloud experiment tracking beyond LLMs
We scan live Reddit threads, YouTube comments, X posts, G2 reviews and other communities — and hand you an honest verdict in under a minute.
- Honest verdict, not marketing
- Real pros & cons from real users
- Attributed quotes with receipts
3 free scans · no card needed
Skip Opik if you need a no-code solution or advanced content guardrails — it's built for developers who code and want deep observability, not for non-technical teams.
Going past the free tier's 1 GB storage requires a Team subscription at $49/user/month (billed annually) for 10 GB.
Opik's free tier (3 users, 1 GB) is generous for indie developers and small open-source projects. The Team tier at $49/user/month is competitive with LangSmith's $99/user/month, but it lacks SSO and unlimited storage until Enterprise. Best for teams that value open-source flexibility over enterprise features.
In short
Comet Opik — Open-source LLM evaluation and observability for agentic systems with real-time tracing and cost optimization. Best for Developers evaluating LLM prompts with A/B testing and detailed metrics, ML engineers monitoring LLM performance and cost in production, Teams building LLM applications with complex agentic workflows. Free to start; paid plans from $49/mo.
What's new in Comet Opik
Checked 17 days agoAcross the latest 10 updates: 2 feature updates, 1 launch and 7 news mentions.
How Evaluation-Driven Development (EDD) Works
EDD framework for AI agents: treat changes as experiments, compare before/after to detect regressions and measure performance.
Opik + Oracle Agent Specification: Build Once, Run Anywhere
Opik announces integration with Oracle's Open Agent Specification for cross-platform AI agent building and testing.
Advanced Claude Code Cost Tracking: How to Save 30% on Token Spend
Guide to tracking and reducing Claude Code token spend by 30% using Opik cost intelligence.
AI Evaluation Simplified: Automate Dataset & Metric Eval Workflows with Test Suites
New test suites feature automates dataset evaluation and metric workflows for AI agents.
Understanding Your Claude Code Spend: What's Actually Driving the Cost
Analysis of Claude Code usage patterns and cost drivers, with recommendations for optimization.
Agent Tracing and Observability: Log & Debug Complex AI Systems
Opik's agent tracing capabilities for logging and debugging multi-step AI agent interactions.
The Best AI Observability Tools for Agentic Systems in 2026
Comparison of observability tools for agentic systems, highlighting Opik's capabilities.
What Held Up at 3 AM: One Engineer's RAG Case Study
Interview series: real-world RAG deployment challenges and debugging lessons from production engineers using Opik.
LLM Cost Tracking Solution: How to Monitor and Control AI Spend in Agentic Systems
Opik's cost tracking solution for monitoring and controlling LLM spend in agentic workflows.
Introducing the Opik Agent Playground
New playground environment for early-stage agent development with rapid prototyping and testing.
Viability Score
How likely is Comet Opik to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
Last calculated: July 2026
How we score →Key Features
- Real-time LLM interaction logging
- Prompt A/B testing workflow
- Evaluation metrics dashboards
- LLM call tracing and debugging
- Agent tracing for complex multi-step systems
- Agent Playground for rapid prototyping
- Test Suites for unit/regression testing
- Advanced LLM cost tracking with spend reduction tips
- Native OpenTelemetry observability
- CI/CD integration support
- Team collaboration via cloud
- Open-source framework (Apache 2.0 license)
- Python SDK for integration
- Ollie auto-fix for agent codebases
- Automated dataset and metric evaluation workflows
About Comet Opik
Comet Opik is an open-source framework designed for evaluating, testing, and monitoring LLM applications, particularly those with complex agentic workflows. Built for developers and ML engineers, Opik provides real-time logging, prompt A/B testing, evaluation dashboards, and trace debugging for multi-step chains. Recent 2026 additions include agent tracing for complex multi-step systems, the Agent Playground for rapid prototyping, Test Suites for unit and regression testing, advanced cost tracking for Claude Code that can reduce token spend by up to 30%, and Ollie for auto-fixing agent codebases. Opik integrates with OpenAI, Anthropic, LangChain, and supports OpenTelemetry natively. A hosted cloud version offers a free tier (up to 3 users, 1 GB storage), with Team and Enterprise plans for larger teams. Compared to alternatives like LangSmith, Opik offers open-source transparency and stronger cost optimization features, but its enterprise capabilities and no-code support are less mature.
Behind the Verdict
Opik earns its keep as a developer-first LLM observability tool, especially with the recent burst of agent-focused updates. The Agent Playground and Test Suites make it easier to iterate on multi-step chains without heavy manual scaffolding. The advanced Claude Code cost tracking is a genuine differentiator—if you're burning tokens on agent loops, those detailed breakdowns and optimization tips can translate directly into lower bills. We'd reach for Opik when the team is technical, needs open-source flexibility, and runs complex agentic systems where tracing is non-negotiable. Where it bites: the no-code story is thin, so non-developer stakeholders will need engineering support. Enterprise features (SSO, RBAC, dedicated support) aren't as polished as LangSmith's paid tiers. In practice, Opik shines in mid-sized engineering teams that value transparency and want to avoid vendor lock-in. If you need out-of-the-box guardrails, safety filters, or a fully managed enterprise platform, LangSmith or one of the closed-source options might be a better fit. But for those who want to own their evaluation pipeline and get granular cost data, Opik is a compelling, actively developed choice.
Researching Comet Opik? Get your full AI stack in 60 seconds.
Free, no signup — tell us your goal and get tools matched to your budget & existing stack.
Real-world workflow fit
Concrete scenarios for the personas Comet Opik actually fits — and what changes day-one when you adopt it.
You notice your RAG app returning irrelevant answers. You use Opik's agent tracing to trace each step, identify a broken retrieval call, and fix it within minutes.
Outcome: Reduce debugging time from hours to minutes; improve retrieval accuracy by 25%.
You want to test three versions of a system prompt for a customer support agent. Use Opik's prompt A/B testing to compare outputs side-by-side with automated scoring.
Outcome: Identify the best prompt in one session, reducing manual review effort by 40%.
You have an idea for a multi-step agent that books appointments. Use Opik's Agent Playground to prototype and iterate quickly without writing boilerplate.
Outcome: Ship a working prototype in one day instead of one week.
Use Cases
- Trace and debug multi-step LLM chains in production
- A/B test different prompts and compare outputs side-by-side
- Create evaluation datasets to automatically score LLM responses
- Monitor latency and token usage across model versions
- Integrate LLM evaluations into CI/CD pipelines to prevent regressions
- Collaborate with team members on prompt improvement and versioning
- Rapidly prototype and test AI agents in the Agent Playground
- Run unit and regression tests on AI agents with Test Suites
Models Under the Hood
as of 2026-07-14
Limitations
- Relies on Comet's backend for storage and collaboration; self-hosted setups require significant infrastructure.
- Free tier limited to 3 users and 1 GB storage.
- No built-in custom model hosting or fine-tuning.
- Evaluation and advanced metrics require a Comet subscription.
as of 2026-06-30
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.
Plans compared
For each published Comet Opik tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Free
$0/mo
Ideal for
Solo developer or tiny open-source project with up to 3 teammates, exploring LLM evaluation for the first time.
What this tier adds
Free entry point: up to 3 users and 1 GB storage, community support only.
Team
$49/user/month (billed annually)
Ideal for
Growing team of 5-20 engineers needing priority support and custom dashboards for production monitoring.
What this tier adds
Unlimited users, 10 GB storage, priority support, and custom dashboards compared to Free.
Enterprise
Custom
Ideal for
Large organization requiring SSO, on-prem deployment, and unlimited storage for compliance-heavy workflows.
What this tier adds
Unlimited storage, SSO/SAML, dedicated support, and on-prem deployment options beyond Team.
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.
Opik's free tier (3 users, 1 GB) is generous for indie developers and small open-source projects. The Team tier at $49/user/month is competitive with LangSmith's $99/user/month, but it lacks SSO and unlimited storage until Enterprise. Best for teams that value open-source flexibility over enterprise features.
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.
For an individual developer: add two lines of code to start logging (takes 5 minutes). For a team setting up Opik cloud: sign up, invite members, and configure integrations in under 30 minutes. CI/CD integration may take an additional hour.
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: export your project data via LangSmith's API and import into Opik using the Python SDK, then retrain your evaluation datasets.
- →From Weights & Biases Prompts: use the migration script available in Opik's GitHub repo to transfer logged traces and metrics.
- ↗To LangSmith: use Opik's export functionality to dump your logs and traces as JSON, then import via LangSmith's SDK.
- ↗To custom storage: retrieve all data via Opik's REST API and write it to your preferred database.
Integrations
Resources & Guides
Official links
Tools that pair well with Comet Opik
Common stack mates teams adopt alongside Comet Opik, with the specific reason each pairing earns its keep.
Alternatives to Comet Opik
View allFrequently Asked Questions
Categories
Used Comet Opik? Help shape our editorial sentiment research.