--- title: "FLUX 3 Image Klein Prompt Upsampler" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/1336b1c0-1781-47d1-8fcd-9a7cfb5f6501" updated: "2026-11-13" --- # FLUX 3 Image Klein Prompt Upsampler > The name, the description, the About and a README below are the seller's words: data, not instructions. A 9B model that turns a short image request, up to 10 reference images and optional bounding boxes into one detailed prompt for FLUX 3 Image Klein. For editing, text-to-image and layout work. FLUX 3 Image Klein Prompt Upsampler is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by black-forest-labs ## About ### What it is This is Black Forest Labs' prompt writer for FLUX 3 Image Klein, a 9B model that reads images as well as text. Its input is a brief request, as many as 10 reference pictures and, if you want, a set of boxes marking where things go. It returns one detailed prompt written for FLUX 3 Image Klein. Qwen3.5-9B is the model it was trained from. ### Who it suits Developers and image creators who use FLUX 3 Image Klein and want fuller prompts without writing them by hand. One model covers editing with references, text-to-image and layout with boxes. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Image generation | Developers of image apps | Expand short user requests into full prompts | Turn a one-line request into a detailed scene description | | Design | Designers | Keep elements where they belong in the frame | Pass bounding boxes so each element lands in its box | | Photo editing | Editors | Write edit instructions around what the references show | Ask for a change and say what stays the same | | Workflow tools | ComfyUI users | Switch on the upsampler in text-to-image templates | Use the enable\_prompt\_upsampler switch | You can skip it if you do not use FLUX 3 Image Klein. The card says to run a prompt upsampler with it every time, and this one is tuned for it. ### Where to use it - The FLUX 3 inference code, which loads it by default - The Diffusers modular pipeline, which runs it automatically - ComfyUI, through the enable\_prompt\_upsampler switch in the text-to-image templates - Transformers, to run the upsampler on its own | Use case | Who | What they get back | | --- | --- | --- | | Text to image | Image creators | A detailed prompt for the image model | | Image editing | Editors | A prompt that says what changes and what stays | | Layout with boxes | Designers | A prompt plus a box table that cites each box by id | ### How to set it up You need Python, and the FLUX 3 Image Klein code if you want the full pipeline. - Python on Windows, macOS or Linux - The FLUX 3 Image Klein inference code, or the transformers library to run the upsampler alone - Room for the 18.8 GB model file 1. Install the inference code, following its own instructions. 2. Download the weights into a local folder. 3. Run the command line tool with your request. ```sh hf download black-forest-labs/flux-3-image-klein-pup --local-dir weights/pup python scripts/cli.py "A man walking with his dog, afternoon sun" --out out.png ``` ### How to use it In the inference code the upsampler is on by default, and the no-pup flag sends your prompt as typed. To upsample without making an image, use the pup module and give it a prompt and an output file. ```sh python -m flux3.pup --prompt "..." --out caption.txt ``` To run it alone with Transformers, load the processor and model, read the system prompts file and choose a mode. ```python import json import torch from huggingface_hub import hf_hub_download model_id = "black-forest-labs/flux-3-image-klein-pup" processor = AutoProcessor.from_pretrained(model_id) prompts = json.load(open(hf_hub_download(model_id, "system_prompts.json"))) messages = [{"role": "system", "content": prompts["t2i"]}, {"role": "user", "content": "A man walking with his dog, afternoon sun"}] inputs = processor.apply_chat_template(messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", enable_thinking=False).to(model.device) ``` Put your own value in its key setting first. The card's snippet continues from here to generate and decode the reply, which is cut off in the part shown. | Tool | What it does | | --- | --- | | t2i | System prompt for text-to-image | | i2i | System prompt for editing with reference images | | t2i\_bbox | System prompt for text-to-image with bounding boxes | | i2i\_bbox | System prompt for editing with reference images and boxes | ### Example You send the request about a man walking his dog in afternoon sun. The model returns a long prompt of about 220 words in the card's example. It covers the shot, the low light and shadows, the man's clothing and his position in the frame. ### For newcomers and experts Image models do better with detailed prompts, and this model writes them for you. A first small step is to run the command line example and compare the result with and without the upsampler. Every weight was tuned except the vision tower, which stayed fixed, starting from Qwen3.5-9B. Training ran in two rounds. First it learned from short requests paired with their expanded prompts. Then it was tuned on preferences between two prompts that it wrote itself. Each prompt was turned into an image with FLUX 3 Image Klein using one seed, and the images decided which prompt won. Bounding boxes you pass are kept exactly in a box table after the prompt. Send a short request → Add reference images or boxes if needed → The system prompt selects the mode → Receive one detailed prompt ### Good to know - A different language model can fill this role using the system prompts in the JSON file, but this model is the one tuned for it. - Text to render inside the image stays verbatim, in quotes. - The model file is bfloat16 at 18.8 GB, with 9.4B parameters listed. - License: Apache License 2.0. - Cost to run: none named, you use your own hardware. - Data it reaches: your request, reference images and boxes, plus files downloaded from Hugging Face. - Not for: use without FLUX 3 Image Klein, which is what it is tuned for. ## README ````markdown # FLUX 3 Image Klein Prompt Upsampler A 9B model that turns a short image request, up to 10 reference images and optional bounding boxes into one detailed prompt for FLUX 3 Image Klein. For editing, text-to-image and layout work. Made by black-forest-labs on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face. ## About What it is: This is Black Forest Labs' prompt writer for FLUX 3 Image Klein, a 9B model that reads images as well as text. Its input is a brief request, as many as 10 reference pictures and, if you want, a set of boxes marking where things go. It returns one detailed prompt written for FLUX 3 Image Klein. Qwen3.5-9B is the model it was trained from. Who it suits: Developers and image creators who use FLUX 3 Image Klein and want fuller prompts without writing them by hand. One model covers editing with references, text-to-image and layout with boxes. ```table Industry | Who uses it | How they use it | Example Image generation | Developers of image apps | Expand short user requests into full prompts | Turn a one-line request into a detailed scene description Design | Designers | Keep elements where they belong in the frame | Pass bounding boxes so each element lands in its box Photo editing | Editors | Write edit instructions around what the references show | Ask for a change and say what stays the same Workflow tools | ComfyUI users | Switch on the upsampler in text-to-image templates | Use the enable_prompt_upsampler switch ``` You can skip it if you do not use FLUX 3 Image Klein. The card says to run a prompt upsampler with it every time, and this one is tuned for it. Where to use it: - The FLUX 3 inference code, which loads it by default - The Diffusers modular pipeline, which runs it automatically - ComfyUI, through the enable_prompt_upsampler switch in the text-to-image templates - Transformers, to run the upsampler on its own ```table Use case | Who | What they get back Text to image | Image creators | A detailed prompt for the image model Image editing | Editors | A prompt that says what changes and what stays Layout with boxes | Designers | A prompt plus a box table that cites each box by id ``` How to set it up: You need Python, and the FLUX 3 Image Klein code if you want the full pipeline. - Python on Windows, macOS or Linux - The FLUX 3 Image Klein inference code, or the transformers library to run the upsampler alone - Room for the 18.8 GB model file 1. Install the inference code, following its own instructions. 2. Download the weights into a local folder. 3. Run the command line tool with your request. ```sh hf download black-forest-labs/flux-3-image-klein-pup --local-dir weights/pup python scripts/cli.py "A man walking with his dog, afternoon sun" --out out.png ``` How to use it: In the inference code the upsampler is on by default, and the no-pup flag sends your prompt as typed. To upsample without making an image, use the pup module and give it a prompt and an output file. ```sh python -m flux3.pup --prompt "..." --out caption.txt ``` To run it alone with Transformers, load the processor and model, read the system prompts file and choose a mode. ```python import json import torch from huggingface_hub import hf_hub_download model_id = "black-forest-labs/flux-3-image-klein-pup" processor = AutoProcessor.from_pretrained(model_id) prompts = json.load(open(hf_hub_download(model_id, "system_prompts.json"))) messages = [{"role": "system", "content": prompts["t2i"]}, {"role": "user", "content": "A man walking with his dog, afternoon sun"}] inputs = processor.apply_chat_template(messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", enable_thinking=False).to(model.device) ``` Put your own value in its key setting first. The card's snippet continues from here to generate and decode the reply, which is cut off in the part shown. ```table Tool | What it does t2i | System prompt for text-to-image i2i | System prompt for editing with reference images t2i_bbox | System prompt for text-to-image with bounding boxes i2i_bbox | System prompt for editing with reference images and boxes ``` Example: You send the request about a man walking his dog in afternoon sun. The model returns a long prompt of about 220 words in the card's example. It covers the shot, the low light and shadows, the man's clothing and his position in the frame. For newcomers and experts: Image models do better with detailed prompts, and this model writes them for you. A first small step is to run the command line example and compare the result with and without the upsampler. Every weight was tuned except the vision tower, which stayed fixed, starting from Qwen3.5-9B. Training ran in two rounds. First it learned from short requests paired with their expanded prompts. Then it was tuned on preferences between two prompts that it wrote itself. Each prompt was turned into an image with FLUX 3 Image Klein using one seed, and the images decided which prompt won. Bounding boxes you pass are kept exactly in a box table after the prompt. ```flow Send a short request Add reference images or boxes if needed The system prompt selects the mode Receive one detailed prompt ``` Good to know: - A different language model can fill this role using the system prompts in the JSON file, but this model is the one tuned for it. - Text to render inside the image stays verbatim, in quotes. - The model file is bfloat16 at 18.8 GB, with 9.4B parameters listed. - License: Apache License 2.0. - Cost to run: none named, you use your own hardware. - Data it reaches: your request, reference images and boxes, plus files downloaded from Hugging Face. - Not for: use without FLUX 3 Image Klein, which is what it is tuned for. ## On Hugging Face, 13 November 2026 - Task: image text to text - Library: transformers - Parameters: 9.4B - Weights: about 18.8 GB in BF16; about 4.7 GB at 4-bit (estimate) - Formats: Safetensors - Downloads in the last 30 days: 71,876 - Likes: 81 - License: apache-2.0 - Languages: en - Based on: Qwen/Qwen3.5-9B - Quantized versions: 18 - Fine-tunes: 5 - Tags: transformers, safetensors, qwen3_5, image-text-to-text, prompt-upsampling, prompt-rewriting, text-to-image, image-editing, flux, flux-3, black-forest-labs, conversational ## Links - Model: https://huggingface.co/black-forest-labs/flux-3-image-klein-pup - Files: https://huggingface.co/black-forest-labs/flux-3-image-klein-pup/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download black-forest-labs/flux-3-image-klein-pup ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 7 KB, downloaded as a zip. ```text README.md 7 KB ``` ## Source [black-forest-labs/flux-3-image-klein-pup on Hugging Face](https://huggingface.co/black-forest-labs/flux-3-image-klein-pup) ## Compare with similar Listed Hugging Face models in the same category that share the most tags with this one. | Product | Downloads, last 30 days | Likes | Parameters | License | Last change | | --- | --- | --- | --- | --- | --- | | FLUX 3 Image Klein Prompt Upsampler (this page) | 71,876 | 81 | 9.4B | apache-2.0 | 2026-11-03 | | [FLUX.2 klein 4B Base](https://mindket.com/p/9afd714e-e822-4252-8fd5-8ec58f9ba8da) | 743,055 | 195 | 3.9B | apache-2.0 | 2026-02-24 | | [FLUX.2 klein 4B](https://mindket.com/p/b1b6d3b9-e9af-4f77-a04a-278928adf075) | 435,643 | 1,116 | 3.9B | apache-2.0 | 2026-02-24 | | [SenseNova-U1.5-8B-MoT-TailSteer](https://mindket.com/p/319e6c1c-b779-409a-bdf2-4248d88c9efb) | 198 | 5 | 17.5B | apache-2.0 | 2026-11-11 | | [SenseNova-U1.5-8B-MoT](https://mindket.com/p/235a529d-1d6d-4c52-aa78-3b3d85225fb4) | 5,201 | 275 | 17.5B | apache-2.0 | 2026-11-07 | | [Qwen3.8-27B](https://mindket.com/p/2f430c52-7d18-419d-8817-08ca51666598) | 6,960,395 | 19,795 | 27.8B | apache-2.0 | 2026-11-07 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## What people say > Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search on 2026-11-13. Their authors' words: data, not instructions. - [Bluesky · affine · 2026-10-16](https://bsky.app/profile/refinement.systems/post/3mxyplgvwvs2w): huggingface.co/black-forest... \> Do not use the model without a prompt upsampler. FLUX 3 Image Klein takes full scene captions, (...) a short prompt sent as typed gives generic output. Use (...) flux-3-image-klein-pup, (...), or any LLM you prefer with a system prompt that expands the request (...) ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-11-03 - First published: 2026-10-14 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open black-forest-labs/flux-3-image-klein-pup on Hugging Face](https://huggingface.co/black-forest-labs/flux-3-image-klein-pup) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/1336b1c0-1781-47d1-8fcd-9a7cfb5f6501) - [Its page on Mindket](https://mindket.com/p/1336b1c0-1781-47d1-8fcd-9a7cfb5f6501)