DeepEval vs Langfuse
DeepEval
deepeval.com
Langfuse
langfuse.comSide by side
| Figure | DeepEval | Langfuse |
|---|---|---|
| Price from | $200/mo | $29/mo |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | Yes | Yes |
| Web | Yes | Yes |
| Windows | Yes | — |
| macOS | Yes | — |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 5 | 10 |
| Spec score · AI LLM Evaluation Tools | 9.4 (#1) | 9.1 (#4) |
| Spec score · Llm Developer Tools | 9.3 (#1) | 8.9 (#4) |
| Spec score · Prompt Engineering Tools | 9.3 (#2) | 9.0 (#5) |
| Documentation | The documentation contains installation, quickstarts, metric references, integrations, tracing, datasets, CLI, environment-variable and troubleshooting sections. | Documentation covers observability, prompt management, evaluation, metrics, APIs, SDKs, integrations, compatibility, deployment, and security with versioned self-hosting guides. |
| Headquarters | San Francisco, California, United States | Berlin, Germany; San Francisco, United States |
| Integrations | Listed integrations include LangChain, Pydantic AI, OpenAI Agents, LangGraph, AWS AgentCore, Strands, Google ADK, LlamaIndex, and CrewAI. | Langfuse lists more than 100 integrations spanning OpenTelemetry, Python and TypeScript, model providers, agent frameworks, gateways, and developer tools. |
| Metrics | The project advertises more than 50 metrics spanning quality, agents, RAG, conversations, safety, voice and multimodal use cases. | Metrics cover quality, cost, latency, and volume, with breakdowns by user, session, geography, feature, model, and prompt version. |
| Rating on G2 | 4.6 out of 5 from 5 reviews | 4.5 out of 5 from 1 review |
| Self-hosting | Confident AI's enterprise service can be deployed on the customer's own infrastructure or used in the vendor cloud. | The OSS edition can be deployed with Docker Compose, Kubernetes Helm, or Terraform guides for AWS, GCP, and Azure, including offline or air-gapped installations. |
| What it does | DeepEval is an open-source framework for testing and evaluating LLM applications locally or in CI/CD. | Langfuse is an open-source AI engineering platform for tracing, prompt management, evaluations, metrics, and iterative improvement of LLM applications and agents. |
Plans
DeepEval
- DeepEvalFree
- FreeFree
- Starter$200 a month
- Team$2,000 a month
- EnterprisePriced on request
Langfuse
- HobbyFree
- HobbyFree
- Core$29 a month
- Core$29 a month
- Pro$199 a month
- Pro$199 a month
- Teams Add-on$300 a month
- Teams Add-on$300 a month
- Enterprise$2,499 a month
- Enterprise$2,499 a month
In their own words
DeepEval
DeepEval is a free, open-source framework for building evaluation pipelines to test AI systems. Its Pytest-native evaluations run in CI/CD or as Python scripts, and the framework lists more than 50 research-backed metrics, including checks for hallucination, faithfulness, answer relevancy, summarization, toxicity and bias. It evaluates text, images and audio, including conversational and voice interactions, using methods such as G-Eval, DAG, QAG and JevEval. DeepEval can generate synthetic goldens from a knowledge base and model conversations across user personas. It also traces agent steps so they can be graded and inspected in a terminal or test runner. Integrations cover agent frameworks including LangChain, Pydantic AI, OpenAI Agents, LangGraph, LlamaIndex and CrewAI, alongside a range of model providers. By default, it sends basic telemetry to PostHog, excluding personally identifiable information and stored results; users can opt out with an environment variable. The maker describes DeepEval OS as for pre-production testing, with results in local files and an engineer-owned test runner. Enterprise capabilities are offered through Confident AI Evals, with self-hosted or maker-cloud deployment options.
Langfuse
Langfuse is an open-source AI engineering platform for teams debugging, analyzing, and iterating on AI agent applications. Its tracing records prompts, model responses, token use, latency, tool calls, retrieval steps, and metadata. Prompt Management stores, versions, deploys, and tests prompts, then links them to traces. Evaluation features include LLM-as-a-judge, code evaluators, user feedback, manual labeling, datasets, and experiments. Integrations include Python and JS/TS SDKs, OpenTelemetry, an API, CLI, MCP Server, and popular AI frameworks. Teams can self-host the MIT-licensed core on customer infrastructure using Docker, with options including Docker Compose, Kubernetes, AWS, and Azure. Langfuse reports annual SOC 2 Type 2 and ISO 27001 audits, external penetration tests, GDPR compliance, a DPA, and a HIPAA-ready region. Its Cloud traffic uses TLS 1.2+ and stored data uses AES-256 encryption. The free Hobby plan is free and includes 50k units per month, 30 days of data access, two users, and community support via GitHub. Core costs $29 a month, billed monthly.