AgentEval vs LangSmith
Detailed side-by-side comparison to help you choose the right tool
AgentEval
🔴DeveloperVoice AI Tools
Comprehensive .NET toolkit for AI agent evaluation featuring fluent assertions, stochastic testing, model comparison, and security evaluation built specifically for Microsoft Agent Framework
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FreeLangSmith
🔴DeveloperBusiness Analytics
LangSmith lets you trace, analyze, and evaluate LLM applications and agents with deep observability into every model call, chain step, and tool invocation.
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💡 Our Take
Choose AgentEval if you want a free, MIT-licensed toolkit with trace record/replay, stochastic evaluation, and 192-probe security scanning running locally in .NET. Choose LangSmith if you need a fully managed observability platform with hosted dashboards, multi-user team collaboration, and deep LangChain/LangGraph integration, and you have budget for LangSmith's per-seat pricing.
AgentEval - Pros & Cons
Pros
- ✓Native .NET integration with full type safety and compile-time error checking, unlike Python alternatives that rely on runtime exceptions
- ✓Red Team module ships with 192 attack probes across 9 attack types covering 60% of OWASP LLM Top 10 2025 with MITRE ATLAS technique mapping
- ✓Stochastic evaluation asserts on pass rates across N runs (e.g., 10 runs at 85% threshold) for statistically meaningful results
- ✓Trace record/replay eliminates API costs in CI — record once with real API, replay infinitely for free with identical outputs
- ✓Model comparison generates markdown leaderboards with cost/1K-request rankings across GPT-4o, GPT-4o Mini, Claude, and other providers
- ✓MIT licensed with explicit public commitment to remain open source forever — no bait-and-switch license changes
- ✓27 detailed samples included from Hello World through Multi-Agent Workflows and Cross-Framework evaluation
- ✓First-class Microsoft Agent Framework (MAF) integration with automatic tool call tracking and token/cost telemetry
Cons
- ✗.NET-only — Python, JavaScript, and Go teams cannot use it and must rely on DeepEval, PromptFoo, or LangSmith instead
- ✗Red Team coverage is 60% of OWASP LLM Top 10, leaving 40% of categories uncovered compared to specialized security scanners
- ✗Commercial/Enterprise add-ons are still in planning phase, so enterprises requiring vendor SLAs and paid support have no tier to purchase
- ✗Small community relative to Python-era evaluation tools means fewer third-party integrations, tutorials, and Stack Overflow answers
- ✗Stochastic evaluation can become expensive — 100 tests × 50 repetitions equals 5,000 LLM calls per run if trace replay is not used
- ✗Tight coupling to Microsoft Agent Framework concepts means evolving with Microsoft's roadmap rather than remaining provider-neutral
LangSmith - Pros & Cons
Pros
- ✓Comprehensive observability with detailed trace visualization
- ✓Native MCP support for universal agent tool deployment
- ✓Generous free tier for individual developers and small projects
- ✓No-code Agent Builder reduces technical barriers
- ✓Managed deployment infrastructure with production-ready scaling
- ✓Strong integration with entire LangChain ecosystem
Cons
- ✗Primarily designed for LangChain applications (limited framework support)
- ✗Steep pricing jump from Plus to Enterprise tier
- ✗Pay-as-you-go model can become expensive for high-volume applications
- ✗Enterprise features require annual contracts
- ✗14-day retention on base traces may be insufficient for some use cases
Not sure which to pick?
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