FluxAI: A Product Suite Overview

Aiming to propel AI development with privacy-focused solutions that grant users control of their data, FluxAI is at the forefront of the intelligence revolution. FluxAI is a suite of AI solutions built using open-source technology for transparent model inference and contextually aware outputs. 

The suite encompasses several AI solutions, the nuances of which can be challenging to grasp. So, if you look at the FluxAI product list and wonder what the “Flux” is, the difference between FluxGPT, FluxONE, FluxINTEL, etc., this article is here to break it down. Let’s dive in!  

FluxGPT

An intuitive chatbot, FluxGPT, runs on open-source LLMs and works similarly to ChatGPT. It is a custom chatbot solution trained on large volumes of text data, which it references to respond to user inputs through natural conversations. 

FluxGPT is built on Meta AI’s Llama architecture and integrates with DeepSeek. FluxGPT offers three current models that users can choose between when chatting: 

• Llama 3.1: This model is quick and reliable, great for most everyday tasks where users require fast outputs.
  
• DeepSeek 32B: This model represents a solid balance of speed and response accuracy. However, due to deep thinking capabilities, model outputs are generally slower than Llama 3.1, but more detailed.
• Qwen3: This model switches between reasoning modes based on user inputs. For more complex tasks and logical reasoning, this model leverages deep-thinking mode and non-thinking mode for basic, general-purpose inputs. 

Note that all current FluxGPT models are updated when new versions are released. For example, we will soon integrate the Llama 4 model architecture. Furthermore, our DeepSeek models feature exposed reasoning, where users can transparently view the AI’s logical thought process when generating outputs. 

Leveraging open-source LLMs ensures transparency: anyone can adopt them, understand how they function, and contribute to their development. Additionally, open-source models are cost-effective, being free to use and deploy. 

With FluxGPT, privacy is guaranteed. No personal data is retained for model retraining, and each conversation stays private because every FluxGPT interaction is entirely isolated. 

When starting a new conversation, Flux chat models cannot reference previous conversations because they don’t store information, so there is no natural data persistence between chats. The only way that FluxGPT can reference previous conversations is if users opt in for the model to save their data through a paid plan.

FluxONE

FluxONE is a responsive text-to-image generator that instantly produces super-quality images depicting realistic lighting, crisp textures, and sharp details based on specific user prompt inputs. High-fidelity imaging refers to the use of AI to generate hyper-realistic and detailed photos, which FluxONE is easily capable of, generating both photorealistic and stylized images. 

FluxONE implements quality image generation across diverse artistic image prompt styles, so whether it be a cartoon, oil painting, or vintage-style picture, users always receive outputs that emphasize detail, clarity, and quality. 

Built using a generative image model developed by Black Forest Labs, FluxONE is designed for speed and rapid processing. It accurately converts most text descriptions into visual images in just 2-6 seconds. However, it’s important to note that usage will impact generation times. For example, larger image resolutions may increase latency. 

Nonetheless, FluxONE offers customizable settings for tailored image generation. Users can customize their image format, size, and aspect ratios and toggle their preferred image quality for unique results. 

FluxONE allows users to “seed” image generation with a unique identifier—usually a number—as a starting point for the generation process. Seeds can be reference guides for the AI, assisting models in producing refined image results when paired with specific prompts. 

FluxONE can handle intense scene complexity, generating intricate image compositions through the Flux.1 text-to-image diffusion model. In image diffusion, a user provides a text prompt to an AI model, describing the image they want to generate. When generating a new image, the AI starts with purely random “noise”—unstructured pixel data with no formation. 

Then, by referencing millions of unstructured image-caption pairs on which its model has been trained, the AI gradually learns how to diffuse the right parts of the noise step by step to reveal an image that matches a given prompt.

FluxONE’s architecture leverages two systems of diffusion: Rectified Flow and Latent Diffusion. Instead of taking multiple steps to diffuse noise, Rectified Flow seeks a direct path from noise to image, significantly reducing the steps needed to filter out the noise. 

Latent diffusion reduces the computations needed for image generation by compressing images into smaller data forms called latent spaces, where the image is reconstructed space by space. By leveraging Rectified Flow and Latent Diffusion simultaneously, FluxONE can instantly generate detailed, high-quality images.

FluxAI API

The FluxAI API is the user’s programmatic entrance to the FluxAI ecosystem. It is an interface all about accessibility that leverages model input/output data for fast information retrieval to enhance application management.  

Code Assist

Code Assist is an AI-powered developer tool that subsidizes coding workloads. Users can leverage generative AI to write code and solve programming problems through natural conversations. 

Code Assist is a personal coding co-pilot that generates code snippets or entire programs based on user language prompts in a chat-style web UI that is accessible and easy to use.

FluxGRADER

FluxGRADER, an AI-powered document evaluation tool, lets users gauge the effectiveness and strength of document messaging and content. A recruiter may have hundreds of resumes to sort through. FluxGRADER will evaluate these resumes, assign grades, and rank them according to relevance to the job title. 

Grades are assigned based on the unique context clients provide through customized descriptions of their documents. For added integrity, FluxGRADER processes uploaded documents entirely in memory and never retains grading results, which are deleted immediately after download. 

FluxGRADER supports batch processing, allowing users to upload ZIP files containing multiple documents for simultaneous evaluation. The AI compares each document to its corresponding user-provided description to determine a grade. FluxGRADER accepts many file formats, including PDF, DOC, DOCX, RTF, TXT, and HTML.

FluxINTEL

FluxINTEL is a document intelligence engine that simplifies and automates document-related tasks by extracting and summarizing key document metadata based on user inputs. Designed for industries handling sensitive information and large data volumes, FluxINTEL processes data locally. 

FluxINTEL delivers enterprise-grade document insights through intelligent iterative questioning. This involves a conversational model that engages an end-user to gauge what data to reference when generating document insights. The model increasingly distills irrelevant data through each round of questioning to construct context-aware, accurate responses to user document queries. 

Conclusion

Catering to any use case within any industry, FluxAI allows users to engage AI in natural conversations to gain context-aware insights, generate high-fidelity images in one click, integrate and deploy their own AI solutions, generate code snippets, objectively evaluate document data, and boost productivity through intelligent insights. 

FluxAI provides decentralized, private solutions built on open-source LLM technology to drive user adoption of artificially intelligent systems. FluxAI’s function is constantly expanding, and soon, products will have referencing capabilities across the suite for more interoperable and seamless workflows. For more information on FluxAI updates, follow us on X and connect with us on Discord!