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Pydantic AI vs Letta

Pydantic AILetta

Bottom line: Pydantic AI for python engineers; Letta for teams that need persistent agent memory.

Pydantic AIPydantic AI

Type-safe Python agent framework from the team behind Pydantic

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LettaLetta

Stateful AI agents with long-term memory (formerly MemGPT).

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Votes00
PricingFreeFreemium
CategoryAgent FrameworksAgent Frameworks
Tags
pythonai-agentstype-safetystructured-outputopen-source
agentsmemoryopen-sourcestateful-agentsllm-framework
Best for
  • Python engineers
  • Production agent teams
  • Data-extraction pipelines
  • Teams that need persistent agent memory
  • Builders of long-running assistants
  • Researchers exploring stateful agents
Pros
  • Schema-first, type-safe outputs
  • Built by the trusted Pydantic team
  • Open source under MIT license
  • Dependency injection makes agents testable
  • Multi-provider LLM support
  • Purpose-built for the agent memory problem
  • Strong research pedigree (MemGPT paper)
  • OS-style tiered memory persists across sessions
  • Open-source core, free to self-host
  • Managed Letta Cloud with free and paid tiers
Cons
  • Python-only, no other language SDKs
  • No no-code or visual builder
  • Smaller ecosystem than the largest frameworks
  • Requires comfort with typing and Pydantic
  • You still pay separately for model usage
  • Narrower than general agent frameworks
  • Often used alongside other tooling, not a full stack
  • Renamed from MemGPT, some older docs use old name
  • Cloud pricing and tiers still evolving
  • Python-focused

Comparison generated from each tool's listing. Add or remove tools above to change it.