DeepAI vs Hy4 preview: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of DeepAI and Hy4 preview — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
DeepAI
DeepAI
All-in-one creative platform offering browser-based generation, editing, chat, video, music and voice tools plus developer APIs.
Key features
- Single-Prompt Multimodal Generation: Generate images, short videos, or music with a single text prompt directly in the browser or via API, enabling rapid creative iterations from one input.
- Photo Editing and Inpainting: Edit and refine images in-browser using prompt-guided edits and masks to change content while preserving surrounding areas.
- Web-Browsing Conversational Agent: Chat with assistants that can browse the internet for up-to-date information and provide sourced responses within the chat interface.
- Voice-Based Realistic Chat: Interact with realistic voice-enabled assistants — speak to the model and receive spoken replies — for voice UI and assistant prototyping.
- Developer APIs and SDKs: Simple REST APIs plus official client libraries (e.g., deepai-js-client) let developers call models, upload files, and configure generation parameters programmatically.
- Moderation and Analysis Models: Prebuilt models such as NSFW detection and other analysis endpoints allow automated content moderation and metadata extraction workflows.
- Configurable Output Parameters: Controls for output count, resolution, and other generation settings (e.g., grid size, width/height) to balance quality, performance, and cost.
- Research & Synthetic Data Tools: Research group and open-source projects (DeepAI Research) provide synthetic-data pipelines and datasets for training and evaluation of multimodal models.
- Hosted model APIs callable by model name (e.g., nsfw-detector, text-generator)
- Official JavaScript client (npm package) and browser distribution (dist/deepai.min.js)
- API key authentication (deepai.setApiKey)
- Supports multiple input types: URL, literal text, and file upload
- Configurable generation parameters (example: width, height, grid size)
- Parameter constraints documented (width/height default 512; acceptable 128–1536)
- Simple call pattern: callStandardApi(modelName, params)
- Open-source repositories and research projects (DeepAI Research, Simverse) available on GitHub
- Integration-friendly: supports bundlers (webpack, browserify) and require('deepai') usage
Best for
- Content Creation for Social Media: Rapidly produce unique images, short videos, and music tracks from prompts for posts, ads, or short-form content without design tools.
- Product/Design Prototyping: Generate concept imagery and iterate visual ideas quickly from text prompts to prototype product aesthetics and UI illustrations.
- Developer Integration: Embed generation, moderation (e.g., NSFW detection) and conversational features into web or mobile apps via the REST API or JavaScript client.
- Voice Assistant Prototyping: Build spoken conversational agents that can both listen and speak, useful for voice interfaces, demos, and accessibility tools.
- Automated Moderation Workflows: Use prebuilt detectors (NSFW and others) to scan user uploads and automate content policy enforcement in platforms and communities.
- Synthetic Data & Research: Leverage DeepAI Research projects (e.g., Simverse) to generate annotated synthetic datasets for training and evaluating computer vision and multimodal models.
- Interactive Educational Tools: Create interactive lessons or creative exercises where students generate and edit images, compose music, or chat with research-capable assistants.
- Automated content moderation (NSFW detection) for images
- Text generation for articles, summaries or copy
- Image generation and configurable outputs for creative assets
- Synthetic dataset generation for computer vision and multimodal research (Simverse)
- Rapid prototyping of ML-enabled web and Node.js applications
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.