Dim Notes vs Laguna by Poolside: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Dim Notes and Laguna by Poolside — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Dim Notes
The Dim (https://www.thedim.app/)
A minimal digital sanctuary for quickly capturing fleeting thoughts and ideas so you don't lose the moment.
Key features
- Quick capture of thoughts and ideas (stated in messaging)
- Minimalist/distraction‑free experience (implied by "sanctuary for your mind")
- Preserve fleeting ideas to prevent loss of inspiration
- Web‑forward presence (Open Graph type: website)
- Simple, focused messaging aimed at personal idea capture
Best for
- Capture fleeting thoughts and ideas before they are forgotten
- Personal journaling and reflection
- Brainstorming and preserving creative ideas
- Lightweight productivity for idea collection and review
Laguna by Poolside
Poolside
Poolside's family of open Mixture-of-Experts foundation models for agentic coding — XS.2 runs locally, M.1 reaches 72.5% on SWE-bench Verified.
Key features
- Two Model Sizes: Laguna XS.2 (33B total / 3B active) and Laguna M.1 (225B total / 23B active) target different latency and capability needs.
- Mixture-of-Experts Architecture: Routes each token through a subset of experts for efficiency at large scale.
- Local Deployment: XS.2 is small enough to run on a Mac with 36 GB of RAM via Ollama under an Apache 2.0 license.
- Strong SWE-bench Results: XS.2 hits 68.2% and M.1 reaches 72.5% on SWE-bench Verified.
- Bundled Coding Agent: Ships 'pool,' a lightweight terminal-based coding agent.
- Agent Client Protocol: Includes a dual ACP client-server used internally for agent RL training and evaluation.
Best for
- Local Agentic Coding: Running XS.2 on a laptop for private, offline code generation and editing.
- High-Capability Code Tasks: Using M.1 for harder, long-horizon software engineering work.
- Self-Hosted Deployments: Building on open weights to avoid third-party API dependencies.
- Research & Fine-Tuning: Adapting permissively licensed weights for custom coding workflows.
- Benchmarking: Evaluating agentic coding performance against SWE-bench Verified and Pro.