LettavsOllama

Full side-by-side comparison — features, pricing, platforms, and which one wins in 2026.

Letta

AI Agent Frameworks

Build stateful AI agents with long-term memory

Full review →Website ↗

Ollama

Local AI Infrastructure

Featured

Run local and cloud LLMs, now including Codex App and CLI workflows

Full review →Website ↗
FeatureLettaOllama
CategoryAI Agent FrameworksLocal AI Infrastructure
PricingFree (open-source) + CloudFree (open-source)
GitHub Stars
13k
✓ More stars
120k
PlatformsLinux, macOS, DockermacOS, Linux, Windows
Key Features
  • ✓ Long-term memory
  • ✓ Stateful agents
  • ✓ Tool use
  • ✓ Multi-model
  • ✓ Self-editing memory
  • ✓ One-command setup
  • ✓ API server
  • ✓ GPU acceleration
  • ✓ Model library
  • ✓ Modelfile
  • ✓ OpenAI-compatible API
  • ✓ Codex App support
  • ✓ Codex CLI launch/profile support
Pros
  • + Solves long-term memory problem
  • + Self-editing memory
  • + Stateful agents
  • + Multi-model support
  • + Active research backing
  • + Dead simple to use with one command
  • + Runs local models offline when hardware fits
  • + OpenAI-compatible API
  • + Huge model library
  • + Official Codex App and Codex CLI integration paths
Cons
  • − Complex memory management
  • − Performance overhead
  • − Rebranding confusion
  • − Still experimental
  • − Requires enough local hardware for larger models
  • − Local coding-agent quality depends heavily on the selected model
  • − Cloud models may require Ollama Cloud subscription or usage costs
  • − No built-in general chat UI without a companion app
Tags
memorystatefulagentsopen-source
open-sourcelocalllminferenceprivacygpucodexcoding-agents

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