LangSmith vs OpenLIT
LangSmith
langchain.comOpenLIT
openlit.ioSide by side
| Figure | LangSmith | OpenLIT |
|---|---|---|
| Price from | $39/mo | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | Yes |
| Web | Yes | Yes |
| Windows | Yes | Yes |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 3 | 3 |
| Spec score · AI Agent Observability Tools | 9.1 (#4) | 8.5 (#9) |
| Spec score · AI LLM Observability Tools | 9.1 (#3) | 8.5 (#8) |
| Spec score · Model Monitoring Software | 9.0 (#4) | 8.4 (#13) |
| Spec score · LLM Observability Tools | 9.0 (#5) | 8.5 (#10) |
| Spec score · Llm Monitoring | 8.9 (#6) | 8.4 (#11) |
| Deployment | Deployment provides managed or self-hosted agent servers with streaming, cron scheduling, authentication, MCP support and more than 30 API endpoints. | The platform can be self-hosted using Docker Compose or Kubernetes Helm and accepts OpenTelemetry data through OTLP. |
| Integrations | Documented integrations cover OpenAI, Anthropic, Bedrock, Gemini, Mistral, LiteLLM, OpenTelemetry, CrewAI, Vercel AI SDK, PydanticAI, AutoGen and many other frameworks and providers. | The home page advertises more than 56 integrations spanning LLMs, agent frameworks, vector databases and GPUs. |
| Rating on G2 | 4.4 out of 5 from 78 reviews. | 5.0 out of 5 from 1 review. |
| SDKs | Official SDK documentation is provided for Python, JavaScript/TypeScript, Go and Java. | Official SDKs are available for Python, TypeScript and Go; Python installs with pip and TypeScript with npm. |
| Self-hosting | Enterprise customers can run LangSmith self-hosted or hybrid on Kubernetes in AWS, Google Cloud or Azure. | Docker Compose runs the UI on port 3000, OTLP receivers on ports 4317 and 4318, and ClickHouse for traces, metrics and logs; Kubernetes Helm deployment is also documented. |
| Support | The Developer plan includes community support, and the Enterprise plan lists a support SLA. | The OSS plan includes community support on GitHub. |
| System requirements | Agent Server deployments require PostgreSQL and Redis; self-hosted installations may use customer-managed PostgreSQL and Redis. | The local sandbox requires Docker and Docker Compose; Kubernetes users install the published Helm chart. |
| Tracing | Tracing records agent conversations and runs step by step, including prompts, model calls, tools, errors, latency and token usage. | LLM tracing can capture calls, tools, and retrievals, with filters for user, session, cost, latency, and metadata. |
| What it does | LangSmith is LangChain's framework-agnostic platform for observing, evaluating and deploying AI agents. | OpenLIT is an OpenTelemetry-native platform for tracing, evaluating, guarding and improving AI agents and coding agents. |
Plans
In their own words
LangSmith
LangSmith is a commercial agent-engineering platform for building, evaluating, deploying, monitoring, and improving AI agents. It supports offline evaluations on curated datasets and real-time scoring of production interactions. Evaluation methods include human review, heuristic checks, LLM-as-judge evaluators, pairwise comparisons, and custom Python or TypeScript evaluators. Annotation queues route runs to subject-matter experts for feedback that can calibrate evaluations, improve prompts, or augment datasets. The Playground compares prompt versions or model providers, and LangSmith chat can auto-improve prompts. Observability includes agent and retrieval tracing, token and general cost tracking, trajectory monitoring, online evaluations, and webhook or PagerDuty alerts. Traces can arrive through SDKs or an API from LangGraph, custom Python, or other stacks; SDKs are listed for Python, TypeScript, Go, and Java. Hosting ranges from cloud to hybrid and self-hosted Enterprise options. The Developer plan costs nothing, Plus costs $39 a month, and Enterprise pricing is custom.
OpenLIT
OpenLIT is an open-source platform for tracing and evaluating LLM activity, managing prompts, and tracking costs. Built on OpenTelemetry, it can capture model calls, tool use, and retrievals, with filters for user, session, cost, latency, and metadata. Evaluations can use an LLM judge, heuristics, or human review on production traffic or experiments. Prompt Hub provides versioning, dynamic variables, API retrieval, unlimited prompt fetching, and AI-assisted improvement. OpenGround supports side-by-side model comparisons for latency, tokens, and cost, including comparisons using a user’s own key. Coding agent monitoring covers sessions, costs, tokens, repository activity, and code impact. The site lists more than 56 integrations across LLMs, agent frameworks, vector databases, and GPUs. OpenLIT accepts OTLP data and can be self-hosted with Docker Compose or Kubernetes Helm. Its Apache 2.0 license and site description note that self-hosting keeps prompts, traces, and secrets in the user’s environment. The OSS plan costs nothing and includes unlimited self-hosted usage, users, projects, and environments.