Backed by a 70ドルM Series C, used by Uber and Booking.com.
Strength: The most genuinely vendor-neutral option. OTel-native means your traces are portable -- you are not locked into Arize's ecosystem. Self-hosting is first-class, not an enterprise upsell. If data residency or compliance matters, this is your safest bet.
Weakness: The eval capabilities are less specialized than DeepEval's metric library. Phoenix started as an observability tool and added eval later, so the eval-specific features (custom metrics, assertion frameworks) are less mature than purpose-built eval tools.
Best for: Teams that need self-hosted, vendor-neutral tracing and eval -- especially those with existing OTel infrastructure or compliance requirements.
Pricing: Free self-hosted (no feature gates). Arize cloud from 50ドル/month.
LangSmith -- Best for LangChain Teams
LangSmith is the eval and observability platform built by the LangChain team. If you are building agents with LangGraph, LangSmith gives you the deepest integration: multi-turn agent evaluation, step-level scoring for each node in your graph, and 400-day trace retention.
The dataset management and annotation features are strong. You can build eval datasets from production traces, annotate them with human labels, and run automated evals against them. The feedback loop between production data and eval quality is well-designed.
Backed by LangChain's 1ドル.25B valuation and used by most LangGraph production deployments.
Strength: Unmatched integration depth with LangGraph and LangChain. If your agents are built on these frameworks, LangSmith provides visibility into every step, every tool call, and every decision point with zero extra instrumentation code.
Weakness: Ecosystem lock-in. LangSmith works best -- and sometimes only -- with LangChain-based agents. If you switch frameworks or use a custom agent architecture, the deep integrations become shallow. The 39ドル/seat/month pricing adds up for larger teams.
Best for: Teams already building with LangGraph or LangChain who want the tightest possible eval and observability integration.
Pricing: Developer plan free. Plus at 39ドル/seat/month. Enterprise pricing on request.
Comet Opik -- Best for Budget and Volume
Comet Opik is the newest entrant positioning itself on two fronts: price and scale. At 19ドル/month for the paid tier (with a generous free plan), it is the cheapest option here. And it handles up to 40 million traces per day, which matters if you are running high-throughput eval pipelines or monitoring agents at scale.
The standout feature is the Agent Optimizer, which uses six different optimization algorithms to automatically improve your agent's prompts and configurations based on eval results. Think of it as automated prompt tuning driven by your eval metrics.
Apache 2.0 licensed, so you can self-host without restrictions.
Strength: The best price-to-capability ratio on this list. The Agent Optimizer turns eval results into actionable improvements automatically, closing the loop between "this prompt scored poorly" and "here's a better prompt." Apache 2.0 licensing gives you full self-hosting flexibility.
Weakness: Newer platform with less enterprise traction and a smaller community than the others. Fewer case studies and production references. The Agent Optimizer is promising but still early -- results vary by use case.
Best for: Teams watching their budget who need production-grade tracing and eval at scale, or teams that want self-hosted eval with a permissive license.
Pricing: Free tier available. Paid plans from 19ドル/month.
How to Choose
The decision depends on three questions:
Do you need eval only, or eval plus production monitoring? If eval-only, DeepEval is the lightest option. If you need both, Braintrust or Arize Phoenix cover the full stack.
Is self-hosting a requirement? Arize Phoenix (free, no feature gates) or Comet Opik (Apache 2.0) are your options. Everything else is cloud-first or enterprise-only for self-hosting.
What is your framework? LangChain teams should start with LangSmith. Everyone else should start with DeepEval (eval-focused) or Braintrust (full lifecycle).
Quick decision tree:
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Open-source + Python? DeepEval
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Full lifecycle + CI/CD gates? Braintrust
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Vendor-neutral + self-hosted? Arize Phoenix
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LangChain ecosystem? LangSmith
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Budget + volume? Comet Opik
The Verdict
The Promptfoo acquisition is a reminder of a principle that applies to every layer of your AI stack: do not depend on a single vendor for critical infrastructure. Today it is your eval tool. Tomorrow it could be your model provider, your hosting platform, or your vector database.
All five tools on this list are either independent companies or open-source projects. Your eval infrastructure should survive any single acquisition.
If you are already writing pytest tests for your agents, DeepEval is the fastest path -- add eval metrics to your existing test suite in an afternoon. If you need a complete platform that covers eval, monitoring, and CI/CD quality gates, Braintrust is the most mature. And if self-hosting is non-negotiable, Arize Phoenix gives you everything for free.
Pick one and start testing. An agent without eval coverage is an agent waiting to break in production.
If you want to go deeper on testing agents at the code level, check out How to Test AI Agent Tool Calls with Pytest. For the frameworks these eval tools pair with, see our Top 5 AI Agent Frameworks for 2026. And for a look at where your agents actually run, here is our Top 5 Code Sandboxes for AI Agents.