README.md

metadata

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 and image editing on Android, with the OpenCL GPU running the DiT. Any size with sides a multiple of 32 works, from 256×256 up; the app offers 7 aspect ratios at three pixel budgets (~512², ~384², ~320²), e.g. 512×512, 576×448, 672×384, 480×320, 384×288.

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

Tested on	Snapdragon 8 Gen 2 (Adreno 740), 16 GB RAM, Android 13
Text to image, 448×576, 20 steps	451 s total (DiT 19.1 s/step on OpenCL fp16)
Image edit, 352×448, 20 steps	348 s total (DiT 12.6 s/step)

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 (int8) / latent (fp16) input projections	36 MB
vae_decoder.mnn	VAE decoder, 64-ch latent → RGBA, fp16 weights, dynamic size	0.5 GB
vae_encoder.mnn	VAE encoder for image editing, RGBA → normalized 64-ch latent, fp16	0.16 GB
text_encoder/	Qwen3-VL-8B-Instruct, MNN int4 (from taobao-mnn/Qwen3-VL-8B-Instruct-MNN). te_config.json runs it text-only; te_vl_config.json adds the vision tower (visual.mnn) for image editing. Both return the last decoder layer before the final norm	5.4 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 image tokens. The cache is one tensor per layer (past_kv_0…past_kv_31): a single [32, 2, P, 32, 128] tensor is exactly 1 MiB per prefix token, and an image-edit prefix (P > 1000) would exceed OpenCL's 1 GiB maximum buffer size on an Adreno 740.

2026-09-23: dit.mnn / dit.mnn.weight were re-exported for that per-layer K/V cache. Older copies do not load with the current runtime — re-download both files.

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).