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license: other
license_name: qwen-research
license_link: LICENSE
base_model:
  - Qwen/Qwen-Image-2.1
base_model_relation: quantized
pipeline_tag: text-to-image
library_name: mnn
tags:
  - mnn
  - android
  - opencl
  - int4
  - qwen-image

Qwen-Image-2.1 · MNN (int4) for Android

Qwen/Qwen-Image-2.1 converted to MNN for on-device text-to-image at 512×512 on Android (OpenCL GPU for the DiT).

Runtime, Android library and demo app: github.com/scsonic/libQwenImage21

Tested on	Snapdragon 8 Gen 2 (Adreno 740), 16 GB RAM, Android 13
512×512, 20 steps	~490 s total (DiT ~19.7 s/step on OpenCL fp16)

Files

Path	What	Size
`dit.mnn` + `.weight`	7B single-stream DiT (32 blocks + norm_out/proj_out). Block linears int4 (block 32), small layers int8	4.5 GB
`txt_in.mnn`, `img_in.mnn`	text / latent input projections (int8)	36 MB
`vae_decoder.mnn`	VAE decoder, 64-ch latent → RGBA, fp16 weights	0.5 GB
`text_encoder/`	Qwen3-VL-8B-Instruct, MNN int4 (from taobao-mnn/Qwen3-VL-8B-Instruct-MNN); `te_config.json` runs it text-only and returns the last decoder layer before the final norm	5.1 GB

Download:

hf download evankuo/Qwen-Image-2.1-MNN --local-dir qwen_image21

How it was made

DiT: taken from the GGUF Q4_K build (leejet/Qwen-Image-2.1-GGUF). Every Q4_K sub-block of 32 weights (w = d·sc·q − dmin·m) maps exactly onto MNN's asymmetric int4 with block 32, so the weights are copied without re-quantization (scales stored as fp16).
Text encoder: Qwen-Image-2.1's text_encoder is byte-identical to Qwen3-VL-8B-Instruct, so the existing MNN export is reused unchanged.
VAE: the residual stream is divided by 256 (exact, power of two) and RMSNorm pre-divides by max|x| so the decoder fits fp16 (it peaks at ~3.5e5 otherwise). The decoded image is unchanged.
The pipeline caches the text K/V once per prompt (Qwen-Image-2.1's block-causal attention), so each denoising step only runs the 1024 image tokens.

Conversion scripts: export/ in the GitHub repo.

License

Derived from Qwen-Image-2.1 and released under the Qwen Research License Agreement (see LICENSE), i.e. for research / non-commercial use under its terms. The text encoder weights come from Qwen3-VL-8B-Instruct (Apache-2.0).