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To run FLUX 3 Image Klein locally, update ComfyUI, accept the Hugging Face access conditions, download the black-forest-labs/flux-3-image-klein-comfy package, place its transformer, text-encoder, prompt-upsampler and autoencoder files where the current ComfyUI template expects them, then open the FLUX 3 Image Klein template and generate with a complete scene caption. Use the distilled checkpoint for normal image generation and editing; use the base checkpoint for fine-tuning, LoRA training and research.
The model is a 5.6-billion-parameter open-weights system for text-to-image and image editing. It can combine up to 10 reference images, render text, follow bounding-box layout instructions and generate at native 4K resolutions. Your practical speed and memory limits depend on precision, resolution, reference-image count, batch size and the exact workflow, because the official material does not set one universal minimum VRAM figure.
What FLUX 3 Image Klein does locally
FLUX 3 Image Klein is designed to run in a ComfyUI workflow on a single consumer GPU. In addition to ordinary text-to-image generation, it supports edits from one reference image, compositions using multiple references, reference-based style transfer, readable text in images, and spatial guidance with bounding boxes. A bounding box uses a 0–1000 coordinate grid to suggest an object’s placement and scale; it is guidance, not a hard pixel mask, so edges can still move during generation.
The model accepts up to 10 reference images. You can therefore provide separate subjects, products, characters or style references and describe how they should be combined. For editing, attach the source image or images in the supplied workflow, then describe the intended change rather than merely naming the object that is already present.
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Native 4K output is supported, but high resolution and multiple references consume substantially more memory than a 1024×1024 test. Start with a small, single-image workflow while validating your installation, then increase resolution, references and batch size one variable at a time.
Before you install
Use a current ComfyUI build
Install or update ComfyUI using its current desktop or manual installation path for your operating system. ComfyUI documents support for Windows, Linux and Apple Silicon macOS, along with model offloading and quantized-model support. An older build may not include the FLUX 3 Image Klein node types, loader options or template, so update before troubleshooting model files.
Plan storage and memory
The Hugging Face package includes more than one large component: base and distilled transformer checkpoints, a text encoder, a prompt upsampler and an autoencoder. Reserve enough disk space for the variants you actually intend to use, plus temporary files and any duplicate formats you download. File size alone is not a reliable estimate of GPU memory use: loaders may expand weights, and activation memory rises with resolution, batch size and reference images.
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No official source gives a universal VRAM minimum. Treat any GPU recommendation as a starting point rather than a guarantee. Quantization, offloading and lower-resolution tests can make a workflow fit on hardware that cannot run the same model at 4K or with a large batch.
Install FLUX 3 Image Klein in ComfyUI
- Update ComfyUI. Launch the current desktop or manual installation and complete its normal update process. Restart ComfyUI after updating so the new nodes and templates are loaded.
- Open the model page on Hugging Face. Find the
black-forest-labs/flux-3-image-klein-comfypackage and accept any access conditions shown for your account. Download the ComfyUI-ready files rather than unrelated checkpoint formats. - Download the required components. Keep the transformer checkpoint you plan to run, the text encoder, the prompt upsampler and the autoencoder. The package supplies both base and distilled transformers; you do not need both for a first generation.
- Place files in the folders used by the template. Open the current FLUX 3 Image Klein template or its node documentation and use the model-folder labels it specifies. Do not guess a folder from another FLUX workflow: the loader must be able to enumerate the exact file type and component.
- Open the template. In ComfyUI, open the Templates panel and load the FLUX 3 Image Klein workflow. The supplied graph should include a standard Load Diffusion Model node, a Load CLIP node configured for type
flux3, a Load VAE node and the prompt-upsampling path. - Select matching files. In the diffusion-model loader, choose the base or distilled transformer you downloaded. In the CLIP loader, choose the supplied text encoder and leave its type set to
flux3. In the VAE loader, select the supplied autoencoder. If a dropdown is empty, the file is in the wrong model directory, the filename extension is unsupported by your build or ComfyUI has not been restarted. - Enable prompt upsampling. Connect and enable the supplied prompt upsampler. The model card explicitly says, “Do not use the model without a prompt upsampler.” A short prompt without expansion can produce generic results; the upsampler turns a brief request into a fuller scene caption. An alternative LLM can perform that expansion, but it must produce a detailed caption that the workflow can pass to the model.
- Run a small first job. Use one prompt, one reference image at most, a modest resolution and batch size 1. Queue the workflow and confirm that it completes before adding 4K dimensions, more references or multiple outputs.
Write prompts that the workflow can use
Describe the complete scene, not just a subject noun. Include the subject, action, setting, camera viewpoint, lighting, materials, color relationships, mood and any legible wording that must appear. Prompt upsampling is intended to supply this scene-level detail, which is why bypassing it often gives generic compositions.
For an edit, state what must remain unchanged and what should be replaced. For example, identify the original subject, preserve its pose and camera angle, then specify the new background, lighting or clothing. When supplying several references, label their roles in the caption (“use reference one for the product shape and reference two for the color palette”) instead of leaving the workflow to infer which image controls which attribute.
For layout control, express each object’s approximate position and size using the workflow’s 0–1000 bounding-box coordinates. Keep in mind that these boxes guide placement and scale; they do not cut out pixels or guarantee a fixed silhouette. If the object drifts, simplify the scene, enlarge the box, or run another pass with a more explicit caption.
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| Checkpoint | Steps and guidance | Best use | Practical implication |
|---|---|---|---|
| Distilled | 16 steps; no guidance | Routine text-to-image generation, image editing and self-hosting | Fewer sampling steps make it the sensible starting point for interactive work and repeated edits. |
| Base | 50 steps; guidance 3.5 | Fine-tuning, LoRA training and research | Expect longer generation than the distilled workflow; select it when training or research control matters more than turnaround time. |
The two checkpoints are not simply “low” and “high” quality modes. Distillation changes the sampling schedule for speed, while the base model is the intended foundation for adaptation work. If you are only creating or editing images locally, start with distilled. If you are preparing a LoRA, fine-tuning the model or reproducing research experiments, use base and its 50-step, guidance-3.5 configuration.
Use quantized variants without guessing at memory
INT8, FP8 and NVFP4 builds are available for this family. Quantization can reduce memory pressure, but each format requires a loader that understands that format. A quantized file will not work merely because it has a smaller filename size or because another loader can open a different precision.
- INT8: useful when the matching ComfyUI loader and hardware path are available; Comfy’s published acceleration test uses INT8 ConvRot with the distilled model.
- FP8: another reduced-precision option, subject to compatible loader and hardware support.
- NVFP4: available as a further quantized variant where the required NVIDIA-compatible loading path is present.
Keep the precision choice consistent across the workflow. If a quantized model fails to load, switch back to a standard supported checkpoint to isolate whether the problem is the file, the loader or the workflow. Quantization may lower memory use, but it does not establish a guaranteed VRAM threshold for every resolution and reference count.
Hardware, speed and realistic expectations
The official launch material describes FLUX 3 Image Klein as running on a single consumer GPU, but it does not define a universal minimum VRAM requirement. Memory fit changes with the following variables:
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- output width and height, especially native 4K;
- batch size;
- number and resolution of reference images;
- base versus distilled step count;
- whether ComfyUI offloads parts of the workflow to system memory.
When memory is tight, first reduce batch size to 1, test at 1024×1024, use the distilled or an appropriate quantized checkpoint, and enable supported offloading. Add references and increase dimensions only after a smaller run succeeds. An out-of-memory error at 4K does not prove that the model cannot run on the GPU; it may mean that this particular combination of precision, references and resolution is too large.
What Comfy’s published benchmark actually shows
In a ComfyUI performance report dated October 15, 2026, pairing INT8 ConvRot quantization with the step-distilled model made 1024×1024 text-to-image generation 4.3× to 9.3× faster than a BF16, 50-step baseline. The report gives these examples:
| GPU | BF16, 50-step baseline | INT8 ConvRot, distilled | Reported change |
|---|---|---|---|
| RTX 5070 | 71 seconds | Under 8 seconds | Within the reported 4.3×–9.3× range |
| RTX 4070 | 78 seconds | Under 9 seconds | Within the reported 4.3×–9.3× range |
These are ComfyUI’s own published tests, not independent measurements. They describe 1024×1024 text-to-image runs under the stated precision and step configurations; they should not be presented as guaranteed times for editing, 4K output, multi-reference compositions or different drivers and loaders.
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Reference images, editing and layout workflows
Single-reference editing
Load one source image in the template’s reference input, then write a caption that separates preserved properties from requested changes. State whether identity, pose, camera framing or text must remain. Run at the source aspect ratio first; only then experiment with a crop or a larger output.
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Multi-reference composition
Attach up to 10 references when the scene needs several subjects or a product-plus-style combination. Give every image a clear role in the prompt. More references increase conditioning information and may increase memory use, so add them incrementally and reduce resolution if the queue runs out of memory.
Text rendering
Put the exact wording in quotation marks in the expanded scene caption and describe its position, material and typography. Inspect the result at full resolution. If lettering is wrong, simplify the surrounding scene and make the text’s location and content explicit before adding more objects.
Bounding-box placement
Use the 0–1000 grid to communicate relative placement and scale—for example, a subject occupying the left half and a product in the lower-right. The coordinates guide composition but are not masks; use a dedicated compositing or inpainting pass when you need pixel-precise boundaries.
Troubleshoot the first failed run
The template or nodes are missing
Update ComfyUI, restart it, and reopen the Templates panel. A model file alone cannot add nodes that an older ComfyUI build does not contain.
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Confirm that the file belongs in the folder named by the current template, that the download completed, and that ComfyUI was restarted after copying it. Verify that the CLIP loader is set to flux3 and that the VAE loader points to the supplied autoencoder.
The workflow produces generic images
Check that the prompt upsampler is enabled and connected. Replace a one-line prompt with a complete scene caption describing subject, environment, lighting, composition and required text. The model card warns against running without an upsampler.
CUDA or memory errors stop the queue
Reduce batch size and resolution, remove extra references, choose the distilled or a compatible quantized checkpoint, and enable supported offloading. Test again at 1024×1024 before restoring features one at a time. If a quantized build fails immediately, use a standard checkpoint to determine whether the loader supports that quantization format.
Results do not follow the box layout
Remember that boxes are soft spatial guidance. Use fewer objects, larger boxes and clearer scale language in the caption. For exact cutouts, finish with a separate mask or compositing workflow rather than expecting the box to behave as a hard mask.
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Commercial use and licensing
The official Comfy Q&A describes the FLUX Kommunity License as free for non-commercial use. It says users and affiliates with annual revenue below US$5 million may use generated images commercially when they filter or review outputs and disclose AI generation where the law requires it. Commercial use outside those conditions—including commercial fine-tuning—requires a license from Black Forest Labs.
Those conditions apply to the license terms, not to a blanket promise that every jurisdiction treats AI-generated material identically. Before publishing, selling or embedding outputs in a product, read the current license text and check the rules that apply to your organization and location. License wording can change, and a model checkpoint’s local availability does not remove those obligations.
Local ComfyUI or a hosted workflow?
Local execution requires your own compatible hardware, storage and setup time, but it keeps the workflow under your control and can operate without uploading source images. A hosted service avoids local GPU management and charges according to its service model, but it introduces account, connectivity, privacy and per-image compute considerations. Choose local ComfyUI when offline processing, repeatable access to your files or control over the workflow is the priority; choose hosting when avoiding hardware setup matters more. Hosted execution is optional and is not required for FLUX 3 Image Klein.
A reliable first-session checklist
- ComfyUI is updated and restarted.
- Access conditions for the Hugging Face package are accepted.
- The transformer, text encoder, prompt upsampler and autoencoder are downloaded.
- Files are in the folders named by the current FLUX 3 Image Klein template.
- The template’s diffusion loader sees the selected checkpoint.
- The CLIP loader uses type
flux3. - The VAE loader uses the supplied autoencoder.
- The prompt upsampler is enabled.
- The first test uses one prompt, one or zero references, batch size 1 and a modest resolution.
- Only after a successful test do you increase resolution, add references or switch precision.
For most local users, the shortest path to a working result is the updated template plus the distilled checkpoint, a compatible standard or quantized loader, and an expanded scene caption. Reserve the base checkpoint and 50-step configuration for training and research, and treat all speed and hardware figures as configuration-specific rather than guarantees.
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