DALL·E 3 vs Hy4 preview: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of DALL·E 3 and Hy4 preview — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
DALL·E 3
OpenAI
State-of-the-art text-to-image generation model that creates high-fidelity images from prompts with ChatGPT integration and safety mitigations.
Key features
- ChatGPT Prompt Rewriting: Automatically reframes, expands, and optimizes terse user prompts through ChatGPT to produce richer, more accurate image generation instructions and enables conversational, iterative edits to refine images.
- Multiple Styles and Quality Tiers: Offers at least two named styles—"vivid" (hyper-real, cinematic) and "natural" (more realistic/blander)—and supports standard and HD quality options to match artistic intent.
- Flexible Aspect Ratios and Sizes: Accepts three official output sizes (1024×1024, 1792×1024, and 1024×1792), allowing vertical or horizontal compositions that change style, framing, and context for different applications.
- Safety Mitigations: Built-in content filters and red-team informed safeguards decline prompts involving named public figures and address visual over/under-representation and other bias-related risks to reduce harmful generations.
- High-Fidelity, Complex Scene Rendering: Improved ability to generate coherent, detailed scenes and fine-grained visual concepts compared to prior DALL·E versions, especially for multi-object and narrative prompts.
- User Ownership Rights: Generated images are made available to creators for reprinting, sale, and merchandising without requiring additional permission from OpenAI.
- API and Platform Integration: Available through OpenAI's product ecosystem (ChatGPT integration, API Generations endpoint, and Azure OpenAI deployments) enabling programmatic image generation and embedding into applications.
- Iterative Editing and Tweaks: Supports conversational touch-ups—users can request simple textual changes to refine composition, color, lighting, and other attributes without rewriting prompts from scratch.
- Generate images from natural language prompts via REST API
- Automatic prompt rewriting/enrichment when integrated with ChatGPT to improve output fidelity
- Two built-in styles: 'natural' and 'vivid' (vivid used by default in ChatGPT)
- Supports multiple output sizes: 1024×1024, 1792×1024, and 1024×1792 (portrait/landscape/aspect variants)
- Quality tiers noted (standard and HD reported) to influence output detail
- Safety mitigations: declines named public-figure generation and reduces harmful/bias outputs (red-team tested)
- Conversational editing: iterative tweaks via ChatGPT-style instructions
- Available via OpenAI Images Generations endpoint (/v1/images/generations) and as deployments in Azure OpenAI
- Compatible with OpenAI official SDKs (e.g., Python SDK v1.x) and used by third-party wrappers and integrations (Bing Image Creator, community SDKs/proxies)
Best for
- Marketing and Ad Creative: Rapidly produce high-quality hero images, social media assets, and ad variations with conversational refinement to match brand voice and campaign needs.
- Concept Art and Storyboarding: Generate cinematic concept art, character studies, and sequential panels for pre-visualization in film, games, and animation with control over aspect ratio and style.
- Product and Packaging Design Mockups: Create visual mockups and merchandising images for prototypes, packaging concepts, and e-commerce listings to accelerate design review cycles.
- Content Illustration and Publishing: Produce book covers, editorial illustrations, and blog visuals tailored via prompt iteration, reducing reliance on stock assets or custom shoots.
- Rapid Prototyping for UI/UX and Design: Create themed imagery and assets for app mockups, landing pages, and pitch decks that align with a desired aesthetic using vivid or natural styles.
- Personalized Merchandise and Prints: Design custom prints, apparel graphics, and other merchandise-ready art where users own the resulting images for commercial use.
- Integrated Creative Assistant in Chat Environments: Use within ChatGPT to brainstorm visual ideas, refine prompts, and produce variations conversationally, streamlining creative workflows.
- Creative asset generation for marketing, ads, and social media visuals
- Concept art, storyboarding, and illustration generation
- Rapid prototyping of product imagery and UI mockups
- Editorial and content creation where tailored images are required
- Integration into chat interfaces for conversational image creation and iterative refinement
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.