ThorVG

Thor Vector Graphics is a production-ready vector graphics engine designed for creating interactive apps and creative tools. It combines high performance with lightweight efficiency, as Thor embodies a dual meaning—symbolizing both immense strength and lightning-fast agility. Embracing the philosophy of simplicity leads to reliability, the ThorVG project provides easy, user-friendly interfaces while maintaining a compact footprint and minimal overhead.

The following primitives are supported by ThorVG:

• Lines & Shapes: rectangles, circles, paths, and arbitrary vector geometry
• Filling: solid colors / linear, radial, and conic gradients
• Stroking: stroke width, joins, caps, dash patterns, and trimming
• Scene Management: retained-mode scene graph and hierarchical transformations
• Composition: W3C compositing and blending modes, masking, clipping, and nested scenes
• Text: unicode, scalable TTF/OTF fonts, and multi-line text layout
• Images: SVG, PNG, JPEG, WebP, and raw bitmaps
• Effects: Gaussian & motion blur, drop shadow, tint, tritone, color replacement, and fill effects
• Animations: Lottie (JSON) playback and rendering

Lightweight Design

​ThorVG is designed for a wide range of programs, offering adaptability for integration and use in various applications and systems. It achieves this through a single binary with selectively buildable, modular components in a building block style. This ensures both optimal size and easy maintenance.

The ThorVG core library can be built with a binary size as small as approximately 170KB. This is significantly smaller compared to graphics engines designed primarily for desktop environments and offers the following advantages.

• Memory Efficiency: Thanks to its low runtime memory usage, ThorVG operates stably even on low-spec systems.
• Fast Boot: The library loads and initializes quickly, improving the overall startup speed of applications.
• Low Size Deployment: With its small code and resource footprint, ThorVG is well-suited for embedded systems, IoT devices, and network-constrained environments.

Broad Portability

ThorVG is based on the C++ standard and provides consistent functionality across various platforms through an abstraction layer that minimizes dependence on specific operating systems or hardware.

• Extensive Platform Support: ThorVG supports web platforms, desktop operating systems such as Windows, macOS, and Linux, mobile platforms including Android and iOS, as well as embedded systems like Tizen and RTOS-based environments.
• Microcontroller Support: ThorVG has been shown to run on microcontrollers like the ESP32, demonstrating its efficiency even within environments with highly limited memory and storage.
• Headless Rendering Support: ThorVG can perform rendering without a display server, enabling use cases such as server-side graphics processing or offline rendering tools.

If your program includes the main renderer, you can seamlessly utilize ThorVG APIs by transitioning drawing contexts between the main renderer and ThorVG. Throughout these API calls, ThorVG effectively serializes drawing commands among volatile paint nodes. Subsequently, it undertakes synchronous or asynchronous rendering via its render-backend engines. Additionally, ThorVG is adept at handling vector images, including formats like SVG and Lottie, and it remains adaptable for accommodating additional popular formats as needed. In the rendering process, the library may generate intermediate frame buffers for scene compositing, though only when essential. The accompanying diagram provides a concise overview of how to effectively incorporate ThorVG within your system.

CPU Rasterization

ThorVG is optimized for CPU-based rasterization, with a strong focus on vector rendering in environments where GPU resources are limited, unavailable, or intentionally avoided. In representative CPU benchmarks, ThorVG demonstrates an average of ~2.9× faster performance to a widely-used vector graphics engine across common vector rendering workloads. The advantage is particularly clear in geometry-heavy scenarios such as rectangles, strokes, rotations, and circle rendering.

SIMD Acceleration

ThorVG provides native SIMD acceleration through AVX2 (x86/x64) and NEON (ARM), further enhancing CPU rasterization performance across supported architectures. These optimizations accelerate key rendering operations, delivering an average performance improvement of approximately 30% across a diverse set of rendering benchmarks. SIMD acceleration is integrated directly into ThorVG's software rendering pipeline, with scalar fallbacks ensuring compatibility across platforms without SIMD support.

Performance Overview

Test Conditions

• Tested with 5k semi-transparent primitives, including shapes, strokes, and images, using alpha blending.
• Image filtering was performed using bilinear interpolation.
• Test Platform: Apple M2 Pro (macOS 26)
• Render size: 2560 × 1440 (2K) for each test case
• Versions: ThorVG v1.1, Skia v148

Threading

ThorVG incorporates a threading mechanism designed to seamlessly retrieve upcoming scenes without unnecessary delays. It utilizes a finely-tuned task scheduler based on thread pools to handle a variety of tasks, including encoding, decoding, updating, and rendering. This architecture ensures efficient use of multi-core processing.

The task scheduler is carefully designed to abstract complexity, simplify integration, and enhance user convenience. Its use is optional, allowing users to adopt it based on their specific needs.

Smart Rendering

ThorVG supports smart partial rendering, which enables more efficient rendering workflows by updating only the portions of a vector scene that have changed. By internally tracking modified regions, it minimizes unnecessary redraws and optimizes overall performance. This feature provides significant benefits in scenarios such as UI rendering, design tools, or applications where large parts of the scene remain static and only small elements update between frames. In such cases, avoiding full-scene rendering can greatly reduce computational workload and improve energy efficiency—making it particularly valuable on mobile and embedd