8 Best OpenAI Evals Alternatives in 2026 (Open Source)

OpenAI Evals — Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.

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

1. 1. DeepEval

   The LLM Evaluation Framework

   What sets it apart: Most comprehensive open-source LLM eval framework with 30+ research-backed metrics including agentic, RAG, multi-turn, MCP, and multimodal — vs Ragas (RAG-only) or custom eval scripts

   Best for: Teams needing comprehensive LLM/agent evaluation pipelines; CI/CD integration for LLM app quality gates; RAG pipeline evaluation and optimization

   ⭐ 18.6kOpenAI Evals vs DeepEval →Full profile →

2. 2. Ragas

   Supercharge Your LLM Application Evaluations 🚀

   What sets it apart: vs manual LLM evaluation: Purpose-built evaluation framework with both LLM-based and traditional metrics, automated test generation, and seamless integration with popular LLM frameworks

   Best for: Evaluating RAG pipeline quality with automated metrics; Generating comprehensive test datasets for LLM apps; Building continuous evaluation feedback loops

   ⭐ 15.9kOpenAI Evals vs Ragas →Full profile →

3. 3. Promptfoo

   Open-source CLI and library for evaluating and red-teaming prompts, agents, RAG systems, and LLM apps

   What sets it apart: Unlike LangSmith (production observability) or Langfuse (logging), promptfoo is the only open-source tool combining eval + red teaming + CI/CD code scanning — now backed by OpenAI while remaining fully MIT-licensed

   Best for: Teams hardening LLM apps against prompt injection and jailbreaks with automated red teaming; Engineering teams adding LLM eval regression tests to CI/CD pipelines

   ⭐ 25.6kOpenAI Evals vs Promptfoo →Full profile →

4. 4. Langfuse

   Open-source LLM engineering platform for observability, evaluation, prompt and dataset management

   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

   ⭐ 35.3kOpenAI Evals vs Langfuse →Full profile →

5. 5. 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

   ⭐ 11.7kOpenAI Evals vs phoenix →Full profile →

6. 6. 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

   ⭐ 4.9kOpenAI Evals vs langwatch →Full profile →

7. 7. 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

   ⭐ 4.8kOpenAI Evals vs Agenta →Full profile →

8. 8. UpTrain

   Open-source platform to evaluate and improve generative AI applications with 20+ preconfigured evaluations

   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

   ⭐ 2.4kOpenAI Evals vs UpTrain →Full profile →