MODEL PROFILE

flux.1dev-abliterated-gguf

raidenzeke · flux.1dev-abliterated-gguf

This is my GGUF quantized version of aoxo/flux.1dev-abliterated. There is no guarantee that this works great, or even correct. Use it at your own discretion. The clip_l.safetensor and ae.safetensor files are directly from aoxo's text_encoder and vae. t5xxl safetensor is merged from shards with this script (https://github.com/soursilver/safetensors-merger), then quantized to FP8 using another script (https://huggingface.co/Clybius/Chroma-fp8-scaled/blob/main/convert_fp8_scaled_stochastic.py). The GGUF is converted from merged shards of safetensor files, then saved via ModelSave node of ComfyUI, converted to GGUF using city96's tool (https://github.com/city96/ComfyUI-GGUF/tree/main/tools), and finally quantized with patched llama-quantize from this tutorial (https://medium.com/@yushantripleseven/convert-flux-models-to-gguf-6a80f6c7377a). I also uploaded a staticly linked binary of that.

Image generationlicense:apache-2.0
Context windowNot disclosed
Input → OutputText → Image
Model weightsNot verified
Profile updated2026/10/31 10:10:32
OVERVIEW

Model overview

This is my GGUF quantized version of aoxo/flux.1dev-abliterated. There is no guarantee that this works great, or even correct. Use it at your own discretion. The clip_l.safetensor and ae.safetensor files are directly from aoxo's text_encoder and vae. t5xxl safetensor is merged from shards with this script (https://github.com/soursilver/safetensors-merger), then quantized to FP8 using another script (https://huggingface.co/Clybius/Chroma-fp8-scaled/blob/main/convert_fp8_scaled_stochastic.py). The GGUF is converted from merged shards of safetensor files, then saved via ModelSave node of ComfyUI, converted to GGUF using city96's tool (https://github.com/city96/ComfyUI-GGUF/tree/main/tools), and finally quantized with patched llama-quantize from this tutorial (https://medium.com/@yushantripleseven/convert-flux-models-to-gguf-6a80f6c7377a). I also uploaded a staticly linked binary of that.

Key features

特点摘要待依据来源补齐,不凭模型名称推断能力。

Limitations & considerations

Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.

PRICING & COST

Source prices & cost analysis

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Estimate monthly base token costs

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INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

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Frequently asked questions

Do open weights permit free commercial use?

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Sources & traceability

许可证:apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。