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Flux2Klein9B

This repository provides a highly optimized, modular deployment ecosystem for the Flux.2 Klein 9B architecture. Structured specifically for advanced pipeline integration within ComfyUI, this repository contains...

Sourcehuggingface.co/geceff/Flux2Klein9B-comfyui/tree/8ff20c8fa709ac55559fe8e88a13092736c42942

TypeOtherModèle de baseblack-forest-labs/FLUX.2-klein-9BVersionCClasse

Source du modèle

Type: Other
Taille du fichier: 16,9 GB
Modèle de base: black-forest-labs/FLUX.2-klein-9B
Version: vBF16
Mis à jour: 6 oct. 2026
Téléchargements: 390
Source: Hugging Face

Description de la source

Flux.2 Klein 9B Custom Ecosystem for ComfyUI

This repository provides a highly optimized, modular deployment ecosystem for the Flux.2 Klein 9B architecture. Structured specifically for advanced pipeline integration within ComfyUI, this repository contains everything required to split workloads, optimize memory layouts, and achieve top-tier generation fidelity under constrained resource environments.

⚠️ CRITICAL NOTICE: BASE MODEL SPECIFICATIONS

🚨 Full-Size Base Models: Please be aware that the primary unquantized base configurations and standard processing pipelines inside this repository have NOT been updated yet to the latest iterations.
💡 Current Architecture: Only the custom-optimized standalone diffusion weights, specialized Turbo/SNOFS parameters, custom text encoders, and streamlined VAE structures are fully deployed, tested, and active.

⚡ Optimal Settings for ComfyUI (Turbo & SNOFS Architectures)

To maximize the structural accuracy of the Flux.2 Klein 9B matrix and eliminate visual artifacts or color bleeding, we strongly recommend bypassing default sampler behaviors and adhering strictly to these optimized parameters:

Parameter	Recommended Value	Note
Sampling Steps	`4 - 12`	Ideal fast-stepping range tailored for Turbo / Distilled / SNOFS workflows
CFG Scale	`0.9 - 2.0`	Crucial: Keep CFG within this low boundary to prevent oversaturation and visual frying
Sampler / Scheduler	`euler` + `simple`	Standard diffusion setup providing the most consistent latent translations

🛠️ Important LoRA Tuning Mechanics:

🔑 The Base + Master Rule: For optimal latent stabilization, it is highly recommended to chain your selected Base Diffusion Model in conjunction with the fulx2vbase-lora-master weight layout. Running the base isolation matrix raw may bypass target structural enhancements.
⚠️ Rank 128 Sensitivity: When deploying the extracted High-Rank variant (flux-2-klein-9b_extracted_lora_rank_128-fp32), be aware that the high-dimensional capacity makes structural tuning significantly harder. It reacts aggressively to minor value shifts. Keep the LoRA strength scale highly constrained (try starting low at 0.3 - 0.6) to prevent sudden convergence collapse or noise corruption.

Screenshot 2026-07-01 114027

Screenshot 2026-07-02 162754

💾 Available Model Variants & Architecture

All assets are cleanly separated into dedicated subdirectories to allow dynamic VRAM loading and modular pipeline configurations:

🎭 1. Core Diffusion Weights (`/diffusion_models`)

These are standalone decoupled diffusion models engineered for high-performance processing, custom LoRA stacking, and split-RAM workflows.

F29b-bf16-master-turbo_v4.safetensors (Thebest of my test 18.2 GB): Maximum fidelity master variant operating in native bfloat16 precision.
F29b-fp8-master-turbo_V4.safetensors (9.43 GB): Optimized 8-bit precision model balancing speed and generation details.
Flux2Klein9B-FP8-turbo.safetensors (9.08 GB): High-efficiency FP8 variant built for extreme fast-turnaround inference loops.
Flux2Klein9B-bf16-turbo.safetensors (18.2 GB): Uncompromised precision edition designed for robust high-VRAM execution.
Flux2Klein9B_base_bf16_SNOFS_v1.4.safetensors (18.2 GB): Fine-tuned SNOFS variant providing unique stylistic control and motion extension boundaries.
Flux2Klein9B_3.0_fp8-turbo.safetensors (9.08 GB): Next-gen iteration compressed for low-VRAM threshold architectures.
Flux2Klein_base-9b-kv.safetensors (18.2 GB): Specialized structural model optimized for extended key-value conditioning layouts.
Flux2Klein_base-bf16_master_v4.safetensors (18.2 GB): Solid foundation checkpoint utilizing clean bfloat16 baseline allocations.
Flux2Klein_master_base_v3.safetensors (18.2 GB): Stable production-grade version 3 weight set.

🗲 2. Supporting Pipeline Components

🔠 Text Encoders (`/text_encoders`)

Contains specialized language models optimized for advanced clip conditioning and prompt adherence:

qwen-3-8b-flux-klein.safetensors (16.4 GB): Full-precision text encoder designed to yield maximum semantic alignment and complex prompt comprehension.
qwen_3_8b_fp8mixed.safetensors (8.66 GB): Mixed FP8 variant engineered to optimize memory utilization and drastically cut down text processing overhead on low-VRAM environments.

🌌 Variational Autoencoders (VAE)

/vae/fulx2vae-master.safetensors: Top-tier full precision FP32 VAE decoder, curated specifically inside the VAE directory to ensure ultimate dynamic range, color accuracy, and artifact prevention during final image decoding.
flux.2vae-bf16.safetensors (Placed in Root): Standard ultra-lightweight bfloat16 VAE (160 MB), made available on the root boundary for rapid, memory-safe execution on constrained GPU environments.

🧩 Custom Extensions (`/loras`)

check by yours.

Sources

1 source

Hugging FacePrincipalVersion 8ff20c8fa709ac55559fe8e88a13092736c42942

huggingface.co/geceff/Flux2Klein9B-comfyui/tree/8ff20c8fa709ac55559fe8e88a13092736c42942

Vérifié 6 oct.

Artefacts du modèle

1 artefact

diffusion_models/F29b-bf16-master-turbo_v4.safetensors

safetensors · BF16 (unverified) · 16,9 GB · SHA-256 5085c05fa34b…004e · Hugging Face

Download file

Extraits de sources

3 extraits

Readme6 oct.huggingface.co/geceff/Flux2Klein9B-comfyui

--- license: apache-2.0 language: - en - zh - th base_model: - black-forest-labs/FLUX.2-klein-9B - black-forest-labs/FLUX.2-klein-9b-fp8 tags: - text-to-image - flux.2 - comfyui - image-to-image - image-editor --- # Flux.2 Klein 9B Custom Ecosystem for ComfyUI This repository provides a highly optimized, modular deployment ecosystem for the **Flux.2 Klein 9B** architecture. Structured specifically for advanced pipeline integration within ComfyUI, this repository contains everything required to split workloads, optimize memory layouts, and achieve top-tier generation fidelity under constrained resource environments. --- ## ⚠️ CRITICAL NOTICE: BASE MODEL SPECIFICATIONS * 🚨 **Full-Size Base Models:** Please be aware that the primary unquantized base configurations and standard processing pipelines inside this repository **have NOT been updated yet** to the latest iterations. * 💡 **Current Architecture:** Only the custom-optimized standalone diffusion weights, specialized Turbo/SNOFS parameters, custom text encoders, and streamlined VAE structures are fully deployed, tested, and active. --- ## ⚡ Optimal Settings for ComfyUI (Turbo & SNOFS Architectures) To maximize the structural accuracy of the Flux.2 Klein 9B matrix and eliminate visual artifacts or color bleeding, we strongly recommend bypassing default sampler behaviors and adhering strictly to these optimized parameters: | Parameter | Recommended Value | Note | | :--- | :--- | :--- | | **Sampling Steps** | `4 - 12` | Ideal fast-stepping range tailored for Turbo / Distilled / SNOFS workflows | | **CFG Scale** | `0.9 - 2.0` | **Crucial:** Keep CFG within this low boundary to prevent oversaturation and visual frying | | **Sampler / Scheduler** | `euler` + `simple` | Standard diffusion setup providing the most consistent latent translations | ### 🛠️ Important LoRA Tuning Mechanics: * 🔑 **The Base + Master Rule:** For optimal latent stabilization, it is **highly recommended** to chain your selected Base Diffusion Model in conjunction with the **`fulx2vbase-lora-master`** weight layout. Running the base isolation matrix raw may bypass target structural enhancements. * ⚠️ **Rank 128 Sensitivity:** When deploying the extracted High-Rank variant (**`flux-2-klein-9b_extracted_lora_rank_128-fp32`**), be aware that the high-dimensional capacity makes structural tuning **significantly harder**. It reacts...

Readme14 juil.huggingface.co/geceff/Flux2Klein9B-comfyui

--- license: apache-2.0 language: - en - zh - th base_model: black-forest-labs/FLUX.1-dev pipeline_tag: text-to-image tags: - text-to-image - flux - flux.2 - comfyui --- # Flux.2 Klein 9B Custom Ecosystem for ComfyUI This repository provides a highly optimized, modular deployment ecosystem for the **Flux.2 Klein 9B** architecture. Structured specifically for advanced pipeline integration within ComfyUI, this repository contains everything required to split workloads, optimize memory layouts, and achieve top-tier generation fidelity under constrained resource environments. --- ## ⚠️ CRITICAL NOTICE: BASE MODEL SPECIFICATIONS * 🚨 **Full-Size Base Models:** Please be aware that the primary unquantized base configurations and standard processing pipelines inside this repository **have NOT been updated yet** to the latest iterations. * 💡 **Current Architecture:** Only the custom-optimized standalone diffusion weights, specialized Turbo/SNOFS parameters, custom text encoders, and streamlined VAE structures are fully deployed, tested, and active. --- ## ⚡ Optimal Settings for ComfyUI (Turbo & SNOFS Architectures) To maximize the structural accuracy of the Flux.2 Klein 9B matrix and eliminate visual artifacts or color bleeding, we strongly recommend bypassing default sampler behaviors and adhering strictly to these optimized parameters: | Parameter | Recommended Value | Note | | :--- | :--- | :--- | | **Sampling Steps** | `4 - 12` | Ideal fast-stepping range tailored for Turbo / Distilled / SNOFS workflows | | **CFG Scale** | `0.9 - 2.0` | **Crucial:** Keep CFG within this low boundary to prevent oversaturation and visual frying | | **Sampler / Scheduler** | `euler` + `simple` | Standard diffusion setup providing the most consistent latent translations | ### 🛠️ Important LoRA Tuning Mechanics: * 🔑 **The Base + Master Rule:** For optimal latent stabilization, it is **highly recommended** to chain your selected Base Diffusion Model in conjunction with the **`fulx2vbase-lora-master`** weight layout. Running the base isolation matrix raw may bypass target structural enhancements. * ⚠️ **Rank 128 Sensitivity:** When deploying the extracted High-Rank variant (**`flux-2-klein-9b_extracted_lora_rank_128-fp32`**), be aware that the high-dimensional capacity makes structural tuning **significantly harder**. It reacts aggressively to minor value shifts. Keep th...

Note6 oct.huggingface.co/geceff/Flux2Klein9B-comfyui

Source context: 390 downloads · 5 likes · Pipeline text-to-image · Library diffusers · Repo geceff/Flux2Klein9B-comfyui