Character AI vs Laguna by Poolside: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Character AI and Laguna by Poolside — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
Character AI
Character.ai
A conversational platform to create, share, and chat with millions of customizable AI characters.
Key features
- Character Library: Browse and interact with millions of user-created characters, each defined by custom personas, backstories, and behavioral prompts to enable diverse conversational experiences.
- Character Creation & Customization: Tools to author new characters by specifying personality, dialogue style, and initial setup so creators can shape how agents speak and act.
- Natural Language Conversation: Open-ended, contextual chat that maintains conversation continuity and adapts responses based on prior messages and character definitions.
- Image Interaction: Ability to send and interpret images within conversations—some characters use image input for recognition, description, or to incorporate visual details into interactions.
- Stateful Memory: Conversations and character state carry contextual memory so characters can reference previous chats, improving continuity and long-form interactions.
- Community Discovery & Sharing: Social features to publish, discover, and reuse characters created by others, supporting exploration and collaborative iteration.
- Unofficial Developer Integrations: Active community-created SDKs and wrappers (Node.js, TypeScript, etc.) that enable programmatic access to chats, character management, and image features for automation and tooling.
- Create, customize and share conversational characters (character cards/profiles).
- Free-form text chat with millions of community-created characters.
- Image features: characters can generate and/or interpret images in conversation contexts.
- Stateful memory: conversations and characters can preserve context/state (examples/demos using Letta show memory-enabled agents).
- Guest authentication and token-based authentication exposed in community SDKs (authenticateAsGuest(), authenticateWithToken()).
- Ecosystem of unofficial APIs and SDKs (Node.js wrapper, Telegram bot integrations, community projects to generate character definitions from corpora).
- Web-first deployment; examples/demos deployed on Vercel and other web hosting platforms.
- Integrations demonstrated with Telegram bots and custom web frontends (e.g., CharacterPlus demo).
- Support for generating character definitions from external text corpora (repos for data-driven character generation).
Best for
- Roleplay & Entertainment: Users can roleplay with fictional characters, celebrities, or original personas for creative entertainment and immersive storytelling.
- Creative Writing & Ideation: Writers and creators can brainstorm dialogue, scenes, or character-driven story ideas by interacting directly with character personalities.
- Prototype NPCs for Games: Game designers can prototype non-player characters with distinct personalities and conversational behavior to test interaction flows.
- Personal Assistants & Companions: Build personalized conversational companions or assistants that remember preferences and maintain ongoing dialogue.
- Education & Tutoring: Create tutor-like characters that present information in tailored voices and styles to help explain concepts or simulate historical figures.
- Developer Experimentation: Use community SDKs and unofficial APIs to automate chats, integrate characters into applications, or conduct research on dialogue behaviors.
- Interactive roleplaying and storytelling with custom characters.
- Prototyping conversational agents and chat-based UIs using community wrappers.
- Building Telegram chatbots that proxy conversations with Character.AI personas.
- Creating stateful, memory-enabled agents for long-running conversations (demo apps using Letta).
- Converting text corpora (books, transcripts) into characters for entertainment or research.
- Embedding character chat experiences into web apps (Vercel, custom frontends).
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.