Humanloop vs LangSmith
Detailed side-by-side comparison to help you choose the right tool
Humanloop
🔴DeveloperLLM evaluation and governance
an LLM development platform for prompt management, evaluations, logging, and trustworthy AI product iteration; the homepage announces the team joining Anthropic.
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DiscontinuedLangSmith
🔴DeveloperAI Observability
LangSmith is LangChain's commercial observability, evaluation and prompt management platform for LLM apps and agents in production.
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FreeFeature Comparison
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💡 Our Take
Choose Anthropic Console (post-Humanloop) if your team is already committed to Claude models and wants tightly integrated evaluation with native access to model internals and reasoning traces. Choose LangSmith if you need a model-agnostic platform supporting Claude, GPT-4, Gemini, and open-source models, want deep integration with the LangChain/LangGraph ecosystem, or are a mid-market team that needs transparent $39/user/month pricing rather than enterprise contracts.
Humanloop - Pros & Cons
Pros
- ✓Pricing page lists a free starting point: 2 members, 50 eval runs, and 10K logs per month.
- ✓Enterprise features include SSO/SAML, role-based access controls, SLA support, and VPC deployment add-on.
- ✓Strong fit for teams that need prompt engineering, evaluations, logs, and trustworthy LLM app iteration.
Cons
- ✗Homepage announces the Humanloop team is joining Anthropic and says the platform is being sunset, so new buyers must verify availability.
- ✗Enterprise pricing is custom and likely requires sales engagement.
- ✗No MCP support was visible in fetched pages.
LangSmith - Pros & Cons
Pros
- ✓Best-in-class integration if you already use LangChain or LangGraph.
- ✓Eval suites are practical enough to actually gate releases on, not just dashboards.
- ✓Self-hosted Enterprise tier covers SOC 2 and regulated environments.
Cons
- ✗Per-trace pricing on Plus surprises teams that scale production traffic quickly.
- ✗Non-LangChain stacks work but trade ergonomic polish for SDK overhead.
- ✗Some eval features require additional LLM spend on top of the platform fee.
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