Comparison

LangSmith vs Pydantic AI

On the evidence we track, Pydantic AI leads this comparison with a composite score of 68/100. Scores are only directly comparable because these tools share a category; the full breakdown and every source is below.

Machine formatsJSONMarkdownGraphQLor send Accept: application/json
LangSmith57
Pydantic AI68
Score
Vioscale score
LangSmith57 / 100low · 12%
Pydantic AI68 / 100medium · 69%
Pricing
Free tier
LangSmith
Pydantic AI
Model
LangSmith
Pydantic AIcommercial
Price level
LangSmith
Pydantic AImid
Starting price
LangSmith
Pydantic AI$49
Transparent
LangSmith
Pydantic AI
Integrations
Count
LangSmith
Pydantic AI7
Security
Disclosure policy
LangSmith
Pydantic AI
Gdpr
LangSmith
Pydantic AI
Hipaa
LangSmith
Pydantic AI
Soc2
LangSmith
Pydantic AI
Reliability
Status page
LangSmith
Pydantic AI
Adoption
Dependent repos
LangSmith
Pydantic AI0
Github stars
LangSmith
Pydantic AI19,517
Package downloads weekly
LangSmith
Pydantic AI3,171,945
Activity
Commits last 30d
LangSmith
Pydantic AI100
Release
Cadence days
LangSmith
Pydantic AI1
History
LangSmith
Pydantic AI20 items
License
Spdx
LangSmith
Pydantic AIMIT
Language
Primary
LangSmith
Pydantic AIPython
Market

Capabilities

Feature-by-feature on the axes that matter for mlops & llmops tools. “-” means undocumented, not absent.

Core
Tool role
LangSmithLLM observability / eval
Pydantic AILLM observability / eval
Deployment
Self-hostable / OSS core
LangSmith
Pydantic AI
Managed cloud available
LangSmith
Pydantic AI
On-prem / VPC deployment
LangSmith
Pydantic AI
Observability
LLM tracing / observability
LangSmith
Pydantic AI
Evaluation (offline / LLM-judge / human)
LangSmith
Pydantic AI
Dev
Prompt management + versioning
LangSmith-
Pydantic AI
Tracking
Experiment tracking / model registry
LangSmith-
Pydantic AI
Serving
Model serving / inference endpoint
LangSmith
Pydantic AI
Interop
OpenTelemetry / OpenLLMetry compatible
LangSmith-
Pydantic AI
Framework-agnostic
LangSmith
Pydantic AI
Gateway
Multi-provider model support
LangSmith-
Pydantic AI
Data
No-train-on-customer-data guarantee
LangSmith-
Pydantic AIUnknown

What each one is

The product in its own terms, so the numbers below have context.

LangSmith

LangSmith enables users to observe, evaluate, and deploy AI agents through a web interface that requires no coding. The platform provides tools for agent engineering and monitoring.

Independently observed

Pydantic AI

Leader

A comprehensive toolkit combining an open-source Python agent development framework with a managed observability platform designed specifically for AI applications, including monitoring, evaluation, and LLM gateway capabilities.

Independently observed

Pricing

List pricing as published by each vendor, with the date we read it. Always verify at the source before you buy.

LangSmith

Pricing not documented yet.

Pydantic AI

Leader
from $49/moHybridFree tier

Free tier (10M spans/month) or paid plans starting at $49/month with usage-based overage at $2 per million spans

  • PersonalFree
    • 10M spans per month included
    • Hard cap to prevent bill shock
  • Team$49/month base + $2.00 per million spans overage
    • Base subscription included
    • Overage billing at flat rate per span
  • Growth$249/month base + $2.00 per million spans overage
    • No seat limits
    • Overage billing at flat rate per span
    • Unrestricted team access
as of verify ↗

Platform & deployment

Where each product runs and how it can be hosted. A dash means undocumented, not unsupported.

Platforms
Web
LangSmith
Pydantic AI
CLI
LangSmith
Pydantic AI
Deployment
Cloud / SaaS
LangSmith
Pydantic AI
Self-hosted
LangSmith
Pydantic AI

Integrations

What each product connects to. Counts come from the vendor's own integration directory where one exists.

LangSmith

Not documented yet.

Pydantic AI

Leader
10 total
  • Pydantic AI
  • Pydantic Evals
  • OpenTelemetry
  • Model Context Protocol (MCP)
  • Snowflake
  • FastAPI
  • OpenAI
  • LangChain
  • HuggingFace
  • Prefect
Independently observed

Comparison generated from independently-sourced facts. Every value links to its source and retrieval date. See the method.