GPT Image 1.5 vs Hy4 preview: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of GPT Image 1.5 and Hy4 preview — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
GPT Image 1.5
OpenAI
Cost-efficient GPT-5 image generator for high-quality visuals, precise edits, and UI designs up to 4× faster.
Key features
- GPT-5 Powered Generation: Uses GPT-5-based image synthesis capabilities to produce detailed visuals and creative outputs with improved semantic understanding.
- Cost-Efficient Processing: Optimized to reduce compute costs per image, enabling larger-scale generation or lower-priced usage for teams and projects.
- Fast Throughput (Up to 4×): Engineered for accelerated image creation and editing workflows, reducing iteration time for designers and content teams.
- Precise Image Edits: Supports targeted edits and refinements to existing images, enabling corrections and modifications without full re-generation.
- UI Design Output: Tailored to generate UI components and mockups, helping product designers rapidly prototype interfaces and visual assets.
- High-Quality Visuals: Focus on producing clean, high-fidelity images suitable for marketing, product imagery, and design presentations.
- Cost-efficient image generation
- High-quality visual outputs
- Precise image edits
- UI design generation
- Up to 4× faster generation throughput
Best for
- Rapid UI Prototyping: Generate multiple UI mockups and component variations quickly to iterate on app and web interfaces during product design sprints.
- Precise Asset Edits: Apply targeted corrections or enhancements to product photos and marketing images without recreating the entire visual.
- High-Volume Visual Production: Produce large batches of marketing visuals or social media imagery while managing compute costs for startups and agencies.
- Design Exploration: Create diverse concept art and visual directions for branding exercises, enabling fast A/B comparisons of styles and layouts.
- Prototype-to-Presentation Workflow: Turn rough design sketches or briefs into polished visuals for stakeholder demos and pitch materials.
- Cost-Conscious Creative Teams: Allow small teams to scale image generation and iteration without incurring high per-image costs.
- Rapid creation of marketing visuals and illustrations
- Iterative UI and product-design mockups
- Precise image edits and refinements
- Fast prototyping of visual assets for applications and websites
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.