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What is Ternary?
Ternary emerges as the pioneering native FinOps solution tailored for optimizing cloud expenditures specifically within Google Cloud. It empowers users to make well-informed financial decisions, fostering a culture of accountability, collaboration, and trust among finance and engineering teams. The FinOps framework is essential for managing the variable costs associated with cloud services, integrating a mix of methodologies, best practices, and cultural adaptations that enhance the value of each dollar spent on cloud resources. Ternary is designed to support organizations at any stage of their FinOps journey, creating tools that effectively connect finance with engineering through features based on FinOps principles. This groundbreaking platform not only offers vital visibility and context but also encourages teamwork, with workflows crafted to enhance responsibility. By allowing organizations to effortlessly monitor, prioritize, and finalize cost-saving measures, Ternary significantly improves overall financial management efficiency. As businesses grow increasingly dependent on cloud technologies, the importance of Ternary in promoting sound financial practices becomes increasingly vital, ensuring that companies can navigate their cloud spending effectively and strategically.
What is Bonsai Image?
The Bonsai Image Ternary 4B MLX 2-bit is a specialized text-to-image diffusion transformer optimized for Apple Silicon, prioritizing high-quality output in its Bonsai Image iteration. By leveraging ternary weights of {−1, 0, +1} alongside FP16 group-wise scaling within its transformer architecture, which includes Q/K/V projections, output projections, and MLP weights, it achieves notable efficiency. This model successfully compresses the FLUX.2 Klein 4B transformer from a hefty 7.75 GB FP16 down to a mere 1.21 GB, resulting in an impressive 6.4× reduction in size while still preserving visual quality and prompt fidelity similar to the original version. The deployment package tailored for Apple Silicon weighs in at 3.88 GB, encompassing the MLX 2-bit diffusion transformer, a 4-bit Qwen3-4B text encoder, and an FP16 Flux2 VAE. Once the text encoder processes the prompt encoding, it is offloaded, ensuring that only the compact transformer and VAE are retained in memory throughout the denoising loop. Additionally, this model incorporates a 4-step FlowMatchEuler sampler with guidance set at 1.0 and a shift of 3.0, effectively eliminating the requirement for CFG and negative prompts, which simplifies the generation process and enhances the overall user experience. Overall, this development marks a noteworthy leap forward in the quest for efficient and high-quality image generation technology, making it accessible for a broader range of applications. Furthermore, the advancements made in this model illustrate the ongoing evolution in the field of machine learning and image synthesis.
Integrations Supported
Cloudera DataFlow
Google Cloud BigQuery
Google Cloud Dataflow
Google Cloud Managed Service for Apache Spark
Google Cloud Platform
Google Cloud Storage
Google Compute Engine
Google Kubernetes Engine (GKE)
Kubernetes
OpenOps
Integrations Supported
Cloudera DataFlow
Google Cloud BigQuery
Google Cloud Dataflow
Google Cloud Managed Service for Apache Spark
Google Cloud Platform
Google Cloud Storage
Google Compute Engine
Google Kubernetes Engine (GKE)
Kubernetes
OpenOps
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Ternary
Company Location
United States
Company Website
ternary.app/
Company Facts
Organization Name
PrismML
Date Founded
2026
Company Location
United States
Company Website
prismml.com
Categories and Features
Cloud Cost Management
Cost Reduction Optimization
Dashboard
Data Import/Export
Data Storage
Data Visualization
Resource Usage Reporting
Roles / Permissions
Spend and Cost Reporting