LangSmith is LangChain's observability and evaluation platform for LLM applications. If you're building with LangChain, LangGraph, or any LLM framework, LangSmith provides the tracing, testing, and monitoring infrastructure you need to ship production AI.
The pricing is straightforward but the value calculation depends on your trace volume and team size. Here's the full breakdown.
LangSmith Pricing Tiers
| Plan | Price | Traces Included | Extra Traces | Seats | Data Retention |
|---|---|---|---|---|---|
| Developer | Free | 5,000/month | Not available | 1 | 14 days |
| Plus | $39/seat/month | 10,000/month | $0.50 per 1,000 traces | Unlimited | 400 days |
| Enterprise | Custom | Custom | Custom | Unlimited | Custom + SSO, SLA |
Developer Plan (Free): What You Get
The free Developer plan is designed for individual builders prototyping and testing LLM applications.
Included Features
- 5,000 traces per month. A trace is a single end-to-end execution of your LLM pipeline, which can include multiple LLM calls, tool uses, and retrieval steps. For a simple chatbot, one user message equals one trace.
- Full tracing and debugging. View every step of your LLM chain: inputs, outputs, latency, token usage, and errors.
- Prompt playground. Test and iterate on prompts directly in the LangSmith UI with side-by-side comparison.
- Basic evaluation. Run evaluations against datasets with built-in and custom evaluators.
- 14-day data retention. Traces older than 14 days are deleted.
Developer Plan Limitations
- Single seat (no team collaboration)
- 5,000 trace cap with no overage option (traces beyond 5K are dropped)
- 14-day retention makes historical debugging impossible
- No organization-level features (SSO, audit logs, RBAC)
Is the Free Plan Enough?
For prototyping and personal projects, yes. 5,000 traces handles roughly 150-200 traces per day. You'll outgrow it when you deploy to production (even moderate traffic exceeds 5K/month) or when you need team access.
Plus Plan ($39/seat/month): The Production Tier
Plus is where most teams land. It removes the Developer plan's constraints and adds production features.
What Changes from Developer
- 10,000 traces included per month, with overage at $0.50 per 1,000 additional traces. No hard cap.
- 400-day data retention. Over a year of trace history for debugging, compliance, and performance trending.
- Unlimited seats. Every team member can access traces, run evaluations, and collaborate on prompt development.
- Annotation queues. Structured workflows for human review of LLM outputs.
- Advanced monitoring. Dashboards, alerts, and performance metrics for production deployments.
- Online evaluations. Run evaluators on production traffic in real-time.
Plus Plan Cost Examples
| Scenario | Monthly Traces | Team Size | Monthly Cost |
|---|---|---|---|
| Small team, light production | 10,000 | 3 | $117 |
| Mid-size team, moderate traffic | 50,000 | 5 | $215 |
| Growing team, heavy traffic | 200,000 | 8 | $407 |
| Large team, high volume | 1,000,000 | 15 | $1,080 |
The math: (seats x $39) + ((traces - 10,000) / 1,000 x $0.50).
Enterprise Plan: Custom Pricing
Enterprise adds security, compliance, and deployment flexibility.
Enterprise-Only Features
- SSO / SAML authentication for enterprise identity management
- RBAC with custom roles and permissions
- Dedicated infrastructure options for data isolation
- SLA with uptime guarantees
- Audit logs for compliance
- Custom data retention policies
- Volume discounts on traces
- Priority support with dedicated account management
Enterprise pricing isn't published. Based on market positioning, expect $1,000-5,000/month minimum depending on team size and trace volume.
LangSmith vs. Alternatives
LangSmith isn't the only LLM observability platform. Here's how it compares.
LangSmith vs. Weights & Biases (W&B)
| Feature | LangSmith | Weights & Biases |
|---|---|---|
| Free tier | 5,000 traces/month | Generous (100GB storage) |
| LLM-specific tracing | Purpose-built | Added via Weave platform |
| LangChain integration | Native (built by same team) | Third-party integration |
| ML experiment tracking | Not included | Industry standard |
| Evaluation framework | Built-in, LLM-focused | General-purpose |
| Best for | LLM-first teams using LangChain | Teams doing both ML and LLM work |
W&B is broader (ML + LLM) while LangSmith is deeper on the LLM side. For a detailed comparison, see our LangSmith vs W&B review.
LangSmith vs. Arize Phoenix
| Feature | LangSmith | Arize Phoenix |
|---|---|---|
| Pricing model | Per-seat + per-trace | Per-seat (cloud) or free (OSS) |
| Open source | No | Yes (Phoenix is open source) |
| Self-hosting | Enterprise only | Free self-hosted option |
| Trace visualization | Excellent | Excellent |
| Best for | Teams wanting managed service | Teams wanting open-source flexibility |
Arize Phoenix is the strongest open-source alternative. Self-host for free to eliminate trace volume costs entirely.
LangSmith vs. Braintrust
| Feature | LangSmith | Braintrust |
|---|---|---|
| Primary focus | Tracing + evaluation | Evaluation + prompt management |
| Free tier | 5,000 traces | 1,000 evaluations |
| AI proxy | No | Yes (route to any model) |
| Best for | Observability-first teams | Evaluation-first teams |
Braintrust emphasizes evaluation and prompt iteration over production monitoring. Its AI proxy feature is unique and useful for A/B testing models.
Do You Need LangSmith?
You Probably Need LangSmith (or an Alternative) If:
- You're running LLM chains with 3+ steps where debugging failures requires seeing intermediate outputs
- You're deploying to production and need to monitor quality, latency, and cost
- You're iterating on prompts and need structured evaluation against test datasets
- Your team has multiple people working on prompts and needs collaboration tools
You Probably Don't Need It If:
- You're making single-step API calls
- You're in early prototyping with no production deployment planned
- Your LLM usage is simple enough that print-statement debugging works
Getting Started
Sign up for the free Developer plan at smith.langchain.com. No credit card required. If you're using LangChain or LlamaIndex, adding tracing takes two lines of code (set environment variables). Framework-agnostic tracing is also supported via the LangSmith SDK.
Start with the free tier. If you hit 5,000 traces before the month is up, that's your signal to evaluate Plus.