Aikimi/Neo-Image-2.1-INT8

Neo Image 2.1 INT8

Built with Qwen. This is an unofficial, weight-only INT8 conversion of Qwen Image 2.1 for Aikimi Studio Neo / Forge Neo. It is not trained, approved, or released by the Qwen team. The original weights and this conversion are subject to the Qwen Research License; use and redistribution are limited to non-commercial research or evaluation under that license. Read NOTICE.md for the required attribution and change notice.

Contents

This repository contains a 7.26 GB diffusion transformer and a 10.02 GB Qwen3-VL text encoder, converted from upstream revision b3179ad355be050328e483a9dfdd9e60cd62adfa. The transformer has 224 bitsandbytes INT8 linear layers; the text encoder has 368. Selected transformer input, modulation, output, and normalization modules retain their source precision. The saved weights use the Diffusers and Transformers save_pretrained() formats, with the quantization configuration recorded in each component.

transformer/ and text_encoder/ contain the saved tensors and configs. release_manifest.json records source revision, conversion recipe, exact runtime versions, file sizes, and SHA-256 hashes. The VAE, processor, scheduler, and unconverted source files are not included.

Use in Forge Neo

The current Neo loader needs the pinned official BF16 model installed first. This release avoids the local INT8 conversion step; it does not currently remove the need to download and retain the official BF16 files. Install Neo's Qwen environment with aikimi-qwen-image21-setup.bat, then run from the Neo root in PowerShell:

& .\venv\Scripts\hf.exe download Aikimi/Neo-Image-2.1-INT8 --local-dir .\tmp\neo-image21-int8
& .\models\Qwen-Image-2.1\worker-env\Scripts\python.exe -X utf8 .\tmp\neo-image21-int8\install.py install --precision int8 --neo-root .

Select INT8 in the Qwen Image 2.1 tab. Neo checks the source revision and runtime versions before installing this release and verifies every downloaded file against release_manifest.json. A subsequent load should report quantized_cache status hit for both components. The installer does not replace an existing saved model. The Diffusers pipeline still needs Neo's isolated runtime and its CPU-offload fix.

Verification and limits

Both saved INT8 components were reloaded after model release without another conversion. A new-image comparison with W4A8 is documented with images and measurements; it is one trial, not a general speed or image-quality guarantee. Persistence validation and conversion details are available in Neo. Quantization can change composition and fine details. CUDA with BF16 support and the versions recorded in the manifest are required by this release's importer.

日本語: Neo向けの非公式変換です。公式のQwen Image 2.1一式を先に導入してから、上記の2コマンドで変換済み重みを取り込みます。再量子化を省けますが、現行のNeoでは元のBF16ファイルも必要です。非商用の研究・評価用途に限る元ライセンスと変更・帰属表示を確認してください。