Character AI vs Hy4 preview: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Character AI and Hy4 preview — 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).
Hy4 preview
Tencent
Tencent's open-weight Hy4 preview, a 770B-parameter Mixture-of-Experts model with 49B active parameters and a 1M-token context window.
Key features
- 770B Mixture-of-Experts Architecture: Holds 770 billion total parameters while activating only 49 billion per token, so capacity scales without proportional inference cost.
- 1M-Token Context Window: Accepts inputs exceeding one million tokens, allowing whole codebases, long document sets or extended agent traces in a single prompt.
- Apache 2.0 Open Weights: Released under a permissive licence that allows commercial use, modification and redistribution with no separate agreement.
- Productivity Task Focus: Tuned for real-world coding, office work and scientific research rather than narrow benchmark optimisation.
- Multi-Product Availability: Accessible globally through Tencent's WorkBuddy, CodeBuddy, Yuanbao and ima applications in addition to the raw weights.
- API Access via TokenHub and OpenRouter: Can be called through Tencent Cloud TokenHub or OpenRouter for teams that prefer hosted inference over self-hosting.
Best for
- Whole-Repository Code Work: Load an entire codebase into the million-token context to reason about refactors and cross-file dependencies at once.
- Long-Horizon Agent Tasks: Drive multi-step agent workflows where the full history of tool calls and intermediate results must stay in context.
- Self-Hosted Deployment: Run a frontier-scale open-weight model on private infrastructure where data cannot leave the organisation.
- Scientific Literature Analysis: Ingest large collections of papers or experimental logs and synthesise findings without chunking the input.
- Office Document Processing: Summarise, draft and restructure long reports, contracts and spreadsheets in enterprise workflows.
- Commercial Fine-Tuning: Adapt the weights for a proprietary product under the Apache 2.0 licence without negotiating a model licence.