Nexus Realistic Vision v5.1 Inpaint MNN INT8
Complete MNN Stable Diffusion 1.5 pack for offline Android text-to-image,
image-to-image, and true 9-channel inpainting. The pack is intended for the
Nexus Android app and its MNN 3.4.1 diffusion runtime.
Contents and provenance
unet.mnn and unet.mnn.weight are an MNN INT8 conversion of the UNet from
SG161222/Realistic_Vision_V5.1_noVAE revision
1e9f017a7b1eaefb63a1900ea6c5953d2739fd21.inpaint_unet.mnn and inpaint_unet.mnn.weight are an MNN INT8 conversion
of the trained 9-channel UNet from
stablediffusionapi/realistic-vision-v51-inpa revision
842b8e36533db07f4f7d421001d423f1788f4a0e.- The tokenizer, text encoder, VAE decoder, scheduler data, and VAE encoder are
the SD1.5-compatible MNN components used by the Nexus mobile runtime.
The dedicated inpaint UNet uses the Nexus MNN diffusion contract:
sample: [2, 9, 64, 64] float32timestep: [1] int32encoder_hidden_states: [2, 77, 768] float32out_sample: [2, 4, 64, 64] float32
The 9 input channels are the noised latent, masked-image latent, and
downsampled mask. Both UNets use 8-bit asymmetric weight quantization.
Pixel 8 Pro validation
The exact four UNet artifacts in this revision were validated through the
production Nexus Studio UI on a Pixel 8 Pro at 512x512 and seed 424242:
- Text-to-image: 30/30 MNN denoise calls in 197.1 seconds produced a detailed,
prompt-aligned blue bird on a branch.
- Inpaint: 30/30 dedicated 9-channel calls in 200.8 seconds produced a
recognizable blue bird inside the white mask while preserving unmasked
pixels.
- Both jobs completed on backend MNN without an app-process restart.
The inpaint MNN output has cosine similarity 0.99999428 against the source
PyTorch UNet for a fixed test tensor (MAE=0.002806, RMSE=0.003535).
Integrity
SHA256SUMS contains hashes for every runtime file. The four model hashes that
distinguish this revision are:
| File | Bytes | SHA-256 |
|---|
unet.mnn | 852,152 | e89e150f8ab15282a26083f30e977e1115ad68effb77f27aed3e0763d6ae4227 |
unet.mnn.weight | 862,468,796 | da0baca8461bab82c479b5bafac7a7fa71e6a452aba6e54cd990dd49ba5d0e92 |
inpaint_unet.mnn | 860,544 | bd4cc664d882b667cb7059ef56d80f1af4a2e2781d9af94b6889114e0a9a9caf |
inpaint_unet.mnn.weight | 862,483,196 | 613751b1d4c6e6fcd3341f341925ef9f55391584fa1b71f52b062b63379c4ba1 |
License
This model inherits CreativeML OpenRAIL-M restrictions from its upstream
Stable Diffusion derivatives. Review the upstream model cards before
redistribution or deployment:
The pack is optimized for mobile correctness and quality, not minimal storage.
Peak memory and speed vary by Android device and MNN backend.
