8 Best Opik Alternatives in 2026 (Open Source)

Opik — Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.. Full-lifecycle LLM platform combining tracing, evaluation, and optimization — uniquely includes Agent Optimizer and Guardrails alongside observability, unlike trace-only tools like LangSmith

These 8 open-source tools do the same job. They are ordered by how closely they match Opik, with live GitHub data so you can see which projects are actively maintained.

ToolGitHub starsStars / 30dLast commit
Opik(original)22.3k+6092026-09-30
Langfuse35.2k+1,8212026-09-30
phoenix11.7k+4182026-09-30
langwatch4.9k+2772026-09-30
helicone6.2k+1342026-09-16
UpTrain2.4k+42024-07-29
Agenta4.8k+1312026-09-30
TensorZero11.7k+902026-06-04
OpenLIT2.8k+772026-09-29
  1. 1. Langfuse

    🪢 Open source LLM engineering platform: LLM Observability, metrics, evals, prompt management, playground, datasets. Integrates with OpenTelemetry, Langchain, OpenAI SDK, LiteLLM, and more. 🍊YC W23

    What sets it apart: Unlike LangSmith (LangChain-specific) or Helicone (proxy-based), Langfuse is fully open-source, framework-agnostic, and self-hostable, combining tracing, prompt management, evaluations, and datasets in a single platform built on ClickHouse for scalable production use.

    Best for: Teams operating production LLM applications who need tracing, prompt management, and evaluation in one platform; Organizations requiring self-hosted LLM observability for data privacy compliance

  2. 2. phoenix

    AI Observability & Evaluation

    What sets it apart: Full-stack AI observability (tracing + eval + datasets + prompt management) in one open-source platform — vs LangSmith which is closed-source and LangChain-specific

    Best for: Debugging and monitoring LLM applications in production; Systematic prompt engineering and experiment tracking

  3. 3. langwatch

    The platform for LLM evaluations and AI agent testing

    What sets it apart: Unified platform combining agent simulation, evaluation, observability, and prompt optimization with OpenTelemetry-native design — vs separate tools for tracing (Langfuse), eval (DeepEval), and prompt management

    Best for: Teams wanting eval + observability + prompt management in one tool; Agent simulation testing before production deployment; Organizations needing OpenTelemetry-native LLM observability

  4. 4. helicone

    🧊 Open source LLM observability platform. One line of code to monitor, evaluate, and experiment. YC W23 🍓

    What sets it apart: vs LangSmith/Braintrust: Combined AI Gateway + Observability platform with one-line integration, generous free tier, unified access to 100+ models, and built-in prompt versioning - Y Combinator backed

    Best for: Teams needing unified observability across multiple LLM providers; Production AI apps requiring cost tracking and prompt management; Developers wanting a single API gateway for 100+ models

  5. 5. UpTrain

    UpTrain is an open-source unified platform to evaluate and improve Generative AI applications. We provide grades for 20+ preconfigured checks (covering language, code, embedding use-cases), perform ro

    What sets it apart: vs generic eval tools: 20+ preconfigured evaluations with customizable prompts, few-shot examples, and scenario descriptions — all running locally for data privacy with root cause analysis on failures

    Best for: RAG system evaluation and quality assurance; LLM application testing before production deployment; Safety and security testing for prompt injection vulnerabilities

  6. 6. Agenta

    The open-source LLMOps platform: prompt playground, prompt management, LLM evaluation, and LLM observability all in one place.

    What sets it apart: Unified open-source LLMOps platform combining prompt playground, version control, 20+ evaluators, and OTel-native observability in one tool — vs separate tools for each

    Best for: Teams needing integrated prompt management + evaluation + observability; Product teams collaborating with SMEs on prompt engineering; Organizations wanting open-source LLMOps alternative

  7. 7. TensorZero

    TensorZero is an open-source LLMOps platform that unifies an LLM gateway, observability, evaluation, optimization, and experimentation.

    What sets it apart: Only LLM gateway that combines inference, observability, evaluation, and optimization in one Rust-based system with data flywheel — vs LiteLLM (routing only) or Langfuse (observability only)

    Best for: Teams wanting a unified LLM gateway with built-in optimization feedback loop; Production systems needing <1ms latency overhead at scale; Organizations wanting to continuously improve LLM performance from production data

  8. 8. OpenLIT

    Open source platform for AI Engineering: OpenTelemetry-native LLM Observability, GPU Monitoring, Guardrails, Evaluations, Prompt Management, Vault, Playground. 🚀💻 Integrates with 50+ LLM Providers,

    What sets it apart: Most comprehensive open-source AI engineering platform — combines observability, 11 evaluation types, rule engine, prompt hub, secret vault, playground, and fleet management in one tool

    Best for: Teams wanting all-in-one LLM platform (observability + eval + prompts + secrets); Organizations needing self-hosted AI engineering platform; Multi-language teams (Python/TS/Go SDK support)