{"title":"Helicone vs LangSmith","slug":"helicone-vs-langsmith","tools":[{"name":"Helicone","slug":"helicone","category":"observability","type":"hybrid","website":"https://helicone.ai","pricing":"freemium","pricing_tiers":["Free (100k requests)","$20/mo Growth","Custom Enterprise"],"open_source":true,"self_hosted":true,"sdk_languages":["python","javascript","typescript"],"frameworks":["langchain","llamaindex","vercel-ai","openai-agents"],"agent_features":{"llm_tracing":true,"cost_tracking":true,"evaluation":false,"prompt_management":false,"real_time_monitoring":true},"compliance":["soc2","gdpr"],"best_for":"Lightweight LLM proxy with cost tracking, caching, and rate limiting — minimal integration effort","limitations":"Proxy-based architecture adds a network hop; less deep tracing than Langfuse; evaluation features are basic","verified_by":"editorial","last_verified":"2026-04-28","source_urls":{"docs":"https://docs.helicone.ai","pricing":"https://helicone.ai/pricing"}},{"name":"LangSmith","slug":"langsmith","category":"observability","type":"cloud","website":"https://smith.langchain.com","pricing":"freemium","pricing_tiers":["Free (5k traces)","$39/seat/mo Plus","Custom Enterprise"],"open_source":false,"self_hosted":false,"sdk_languages":["python","javascript","typescript"],"frameworks":["langchain"],"agent_features":{"llm_tracing":true,"cost_tracking":true,"evaluation":true,"prompt_management":true,"real_time_monitoring":true},"compliance":["soc2","gdpr"],"best_for":"Deep tracing and evaluation for LangChain-based agents — tightest integration with the LangChain ecosystem","limitations":"Heavily coupled to LangChain; no self-hosted option; closed-source; less useful if you're not using LangChain","verified_by":"editorial","last_verified":"2026-04-28","source_urls":{"docs":"https://docs.smith.langchain.com","pricing":"https://www.langchain.com/pricing"}}],"category":"observability","last_verified":"2026-05-09","body":"Helicone and LangSmith serve different depths of agent observability. LangSmith provides deep run-tree tracing, evaluation pipelines, prompt engineering, and dataset management. Helicone provides proxy-based request logging with cost tracking and gateway features. LangSmith wins on all three dimensions. Helicone wins on zero-code integration and cost analytics.\n\n## Where LangSmith wins\n\n* **Deep run-tree tracing with auto-instrumentation across agent frameworks.** LangSmith captures nested run trees showing the full agent execution path: orchestrator decisions, tool calls, retrieval steps, sub-agent delegations, and LLM calls with inputs, outputs, tokens, and latency. Auto-instrumentation for LangChain, LangGraph, OpenAI, Anthropic, CrewAI, Vercel AI SDK, and Pydantic AI provides this without manual annotation. Helicone's Sessions group requests into hierarchical paths via manual HTTP headers. Helicone does not auto-instrument agent frameworks and does not capture tool-call arguments, retrieval documents, or orchestrator decision logic as trace-level data.\n\n* **Comprehensive evaluation with four evaluator types and dataset management.** LangSmith provides LLM-as-judge, code-based rules, human review, and pairwise comparison evaluators. Datasets can be curated manually, generated from production traces, or created synthetically. Offline experiments run evaluators against datasets with configurable repetitions. Online evaluation monitors production traces with sampling controls. Multi-turn evaluation captures dialogue quality across turns. Helicone accepts scores from external evaluators via API. It does not run evaluators, manage datasets, or support experiment workflows. The evaluation logic, dataset curation, and experiment execution must all be built outside Helicone.\n\n* **Prompt engineering with versioning, playground, and deployment.** LangSmith provides prompt versioning, a collaborative playground, and deployable prompt artifacts testable against datasets. Prompts iterate through the observe → evaluate → improve cycle within a single platform. Helicone has no prompt management features.\n\n## Where Helicone wins\n\n* **Zero-code proxy integration with cost tracking across 100+ models.** Helicone integrates by changing the base URL—no SDK, no callbacks, no manual instrumentation. Every LLM request is logged automatically with cost attribution across OpenAI, Anthropic, Google, Groq, Vertex AI, and 100+ other models. Cost dashboards show spend by model, user, and time period. LangSmith captures token counts and cost for instrumented frameworks. The integration requires SDK installation and configuration. Helicone's proxy model provides cost visibility faster and across a broader model catalog.\n\n* **AI gateway features for production reliability.** Helicone's proxy enables request caching (deduplicate identical prompts), automatic provider fallbacks, rate limiting, and unified provider billing. These gateway-level features reduce cost and improve reliability without application code changes. LangSmith is an observability and evaluation platform — it does not intercept requests, cache responses, or provide provider fallback routing.\n\n## The agentic difference\n\nLangSmith provides the agent development lifecycle: trace runs, evaluate output quality, iterate on prompts, run experiments, deploy improvements. Helicone provides LLM request visibility: log calls, track costs, optimize at the gateway level. They operate at different layers of the agent stack.\n\nFor teams building and improving agent systems—debugging why an agent produced a wrong answer, comparing prompt versions against evaluation datasets, annotating production traces for quality—LangSmith provides the workflow. For teams that need immediate cost visibility across all LLM providers with zero integration effort, and can handle evaluation and prompt iteration separately, Helicone provides that layer.\n\n## When to pick which\n\n* **Pick LangSmith** when the team needs deep agent chain tracing, evaluation pipelines (LLM-as-judge, human review, experiments), prompt management, and dataset-driven testing — the core agent quality improvement workflow.\n\n* **Pick Helicone** when the priority is zero-code LLM cost tracking across many providers, gateway-level caching and fallbacks, and the team handles evaluation and prompt management with separate tools."}