8 Best MLflow Alternatives in 2026 (Open Source)
MLflow — The open source AI engineering platform for agents, LLMs, and ML models. MLflow enables teams of all sizes to debug, evaluate, monitor, and optimize production-. The largest open source AI engineering platform with comprehensive observability and evaluation features specifically designed for agents and LLM applications.
These 8 open-source tools do the same job. They are ordered by how closely they match MLflow, with live GitHub data so you can see which projects are actively maintained.
| Tool | GitHub stars | Stars / 30d | Last commit |
|---|---|---|---|
| MLflow(original) | 28.2k | +2,350 | 2026-09-30 |
| Langfuse | 35.2k | +1,821 | 2026-09-30 |
| phoenix | 11.7k | +418 | 2026-09-30 |
| Opik | 22.3k | +609 | 2026-09-30 |
| langwatch | 4.9k | +277 | 2026-09-30 |
| Agenta | 4.8k | +131 | 2026-09-30 |
| OpenLIT | 2.8k | +77 | 2026-09-29 |
| TensorZero | 11.7k | +90 | 2026-06-04 |
| helicone | 6.2k | +134 | 2026-09-16 |
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. 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. Opik
Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.
What sets it apart: Full-lifecycle LLM platform combining tracing, evaluation, and optimization — uniquely includes Agent Optimizer and Guardrails alongside observability, unlike trace-only tools like LangSmith
Best for: Teams needing end-to-end LLM observability from development to production; Automated LLM evaluation and quality assurance in CI/CD pipelines
4. 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
5. 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
6. 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)
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. 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
FAQ
- What are the best alternatives to MLflow?
- The closest open-source alternatives to MLflow are Langfuse, phoenix and Opik, followed by langwatch, Agenta and OpenLIT. They are ranked by how closely they match what MLflow does.
- Which MLflow alternative is the most popular?
- Langfuse has the most GitHub stars among MLflow alternatives, with 35,238 stars.
- Which MLflow alternative is the most actively maintained?
- By recent activity, Agenta (8,984 commits in the last 90 days) is the most actively developed alternative.