Wonder 3.5 — New!

Highest-quality generative upscaling for images with greater detail, precision, and realism

Model Overview

Wonder 3.5 is an updated generative upscaling model designed to deliver higher levels of detail, precision, and natural realism across a wide range of image types. It supports both high-quality inputs and heavily degraded or compressed images, with selectable Low, Medium, and High enhancement levels for greater control across varying input conditions.

Building on Wonder 3, Wonder 3.5 produces finer detail with fewer repetitive patterns and improved handling of visual noise. It also delivers greater precision when enhancing structured graphics such as tables and charts, while maintaining strong performance across portraits, landscapes, wildlife, and complex textures.

Key Capabilities

• Higher-quality results with increased detail and improved realism.
• Transformative enhancement for low-resolution and compressed photos, with improved detail and text clarity.
• Fewer repetitive patterns and improved handling of visual noise.
• Greater precision for tables, charts, and other structured graphics.
• Low, Medium, and High enhancement controls for a range of input conditions.

Model Pricing

Output MP	1	4	8	16	24	32	40	50	64	100
Credits	1	1	1	2	3	4	5	7	8	13

Getting Started

Endpoint

• https://api.topazlabs.com/image/v1/enhance-gen/async

  • model — "Wonder 3.5"

Model-Specific Parameters

• enhancement_strength — enum (optional), default "high"

  • Enhancement strength (low, medium, high)
• grain — boolean (optional), default false

  • Whether to add grain to the output
• grain_density — number (optional), default 0.5

  • Intensity of the grain effect (0.0 to 1.0)
• grain_model — string (optional), default "silver"

  • Grain model: 'silver', 'gaussian', 'grey'
• grain_size — number (optional), default 1.0

  • Size of the grain particles (1 to 5)
• grain_strength — number (optional), default 0.5

  • Strength of the grain effect (0.0 to 1.0)
• input_height — integer (optional), default null

  • Input image height in pixels
• input_width — integer (optional), default null

  • Input image width in pixels
• output_height — integer (optional), default null

  • Output image height in pixels
• output_width — integer (optional), default null

  • Output image width in pixels

Examples

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