Winnougan/Klein-9b-kv-mxfp8

Model Card for Klein-9B KV (MXFP8 / NVFP4)

Quantized KV-cache optimized variant of FLUX.2 Klein 9B for faster and more memory-efficient image generation.

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Model Details

Model Description

Klein-9B KV (MXFP8 / NVFP4) is a quantized version of FLUX.2 Klein 9B with KV-cache support for improved performance in multi-reference and iterative workflows.

• Developed by: Black Forest Labs (base), Winnougan (quantization)
• Model type: Text-to-image / image-to-image generative model
• License: Apache-2.0 (repo), base model license applies
• Finetuned from model: FLUX.2-klein-9b-kv-fp8

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Model Sources

• Repository: https://huggingface.co/Winnougan/Klein-9b-kv-mxfp8

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Uses

Direct Use

• Text-to-image
• Image-to-image
• Multi-reference workflows (KV-cache)

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Out-of-Scope Use

• Factual or reliable information generation
• Safety-critical applications

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Bias, Risks, and Limitations

• May reflect biases from training data
• Minor quality loss due to quantization
• KV benefits require compatible workflows

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Recommendations

Use MXFP8 for better quality and NVFP4 for maximum performance. KV-cache is most effective in iterative workflows.

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How to Get Started with the Model

Load in a KV-compatible pipeline (e.g., ComfyUI) and reuse reference images to benefit from KV-cache.

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Training Details

Training Data

Inherited from FLUX.2 Klein 9B. No additional training.

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Training Procedure

Post-training quantization:

• MXFP8
• NVFP4
• KV-cache enabled

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Evaluation

Results

• Faster inference with KV-cache
• Reduced VRAM usage
• Small quality trade-offs depending on format

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Technical Specifications

• ~9B parameters
• Rectified Flow Transformer
• 1024×1024 resolution

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Model Card Authors

Winnougan