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Description
The Bonsai Image Ternary 4B MLX 2-bit is a text-to-image diffusion transformer specifically designed for deployment on Apple Silicon, emphasizing quality in its Bonsai Image variant. This model utilizes ternary weights of {−1, 0, +1} along with FP16 group-wise scaling in its transformer layers, which encompass Q/K/V projections, output projections, and MLP weights. Notably, it reduces the size of the FLUX.2 Klein 4B transformer from 7.75 GB FP16 to just 1.21 GB, achieving a remarkable 6.4× smaller footprint while maintaining visual quality and fidelity to prompts akin to the original model. The deployment package for Apple Silicon is 3.88 GB, which includes the MLX 2-bit diffusion transformer, a 4-bit Qwen3-4B text encoder, and an FP16 Flux2 VAE. After the text encoder handles prompt encoding, it is offloaded to ensure that only the compact transformer and VAE remain in memory during the denoising loop. Furthermore, the model employs a 4-step FlowMatchEuler sampler with guidance set at 1.0 and a shift of 3.0, eliminating the need for CFG and negative prompts, thus streamlining the generation process for enhanced user experience. Overall, this innovation represents a significant advancement in efficient and effective image generation technology.
Description
Qwen-Image 3.0 represents the third iteration of the foundational image generation model in the Qwen-Image lineup, designed to enhance the transition from visually attractive outputs to practical, information-dense creations. This model is focused on achieving three primary objectives: producing rich content, ensuring authentic details, and harnessing deep knowledge. It allows users to submit prompts of up to 4.5K tokens, enabling detailed descriptions of intricate layouts, precise text, hierarchical structures, relationships, styles, and multiple sections within a single request. Notably, it excels at generating complex content types such as multi-panel infographics, newspaper layouts, storyboards, examination papers, presentation grids, academic documents, nested interfaces, posters, and other structured visuals all in one go, instead of requiring the assembly of separate images. Furthermore, Qwen-Image 3.0 enhances text rendering capabilities, accommodating legible characters as small as 10 pixels, supporting twelve different languages, and proficiently reproducing intricate LaTeX formulas, labels, paragraphs, handwritten notes, and mixed-language formats. This combination of features allows for a seamless and versatile approach to image generation, making it a powerful tool for various creative and academic applications.
API Access
Has API
API Access
Has API
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
PrismML
Founded
2026
Country
United States
Website
prismml.com
Vendor Details
Company Name
Alibaba
Founded
1999
Country
China
Website
qwen.ai/blog