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AbrahamPJ/
neodragon-npu-s25u

Name: neodragon-npu-s25u
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Neodragon on Snapdragon 8 Elite (SM8750) — QNN context binaries

Pre-compiled QAIRT / QNN context binaries for the Neodragon autoregressive text-to-video pipeline, targeting the Hexagon HTP v79 NPU in the Samsung Galaxy S25 Ultra (SM8750).

These are the exact artefacts the companion Android app loads at runtime. They are device-specific: compiled for soc_model 69 / HTP v79. They will not load on a v75 or earlier Hexagon.

13 binaries. The three mmdit_*fs graphs replace the older mmdit_s0g/s1f/s2f, which may still be present for rollback.

file	bytes	role
`mmdit_s0fs_v79.bin`	1,525,163,128	Pyramidal MMDiT, stage 0 (408 tokens)
`mmdit_s1fs_v79.bin`	1,533,523,064	Pyramidal MMDiT, stage 1 (648 tokens)
`mmdit_s2fs_v79.bin`	1,573,344,888	Pyramidal MMDiT, stage 2 (1728 tokens)
`quicksrm2x_v79.bin`	377,880	QuickSRNet Medium 2x, 320x512 -> 640x1024
`ctxadaptfp16_v79.bin`	260,531,784	Context adapter (FP16)
`distilt5f_v79.bin`	260,050,504	DistilT5 text encoder
`vaeenc_v79.bin`	41,667,768	Causal video VAE encoder
`vaedecsn_v79.bin`	12,104,632	Causal video VAE decoder (streaming, NHWC states)
`clipl_v79.bin`	233,993,824	CLIP L (first-frame path)
`cliplp_v79.bin`	249,451,112	CLIP L with projection (video path, pooled)
`clipg_v79.bin`	1,402,277,416	CLIP G
`ssd1bunet_v79.bin`	1,358,184,480	SSD-1B UNet (LCM, 4 steps)
`ssd1bvaedec_v79.bin`	85,467,216	SSD-1B VAE decoder

The *fs MMDiT binaries supersede mmdit_s0g / s1f / s2f. They contract the attention score once at full width instead of as two half-width MatMuls plus an add. That is arithmetically identical in fp32 (126 dB against the stock model) but avoids quantising two large, partially-cancelling terms separately -- worth +10.9 / +12.2 / +12.0 dB, and it puts every stage past its paper target for the first time. Accelerator cycles fall 4.4% as well.

Byte sizes are load-bearing: the app verifies every download by exact length. Large transfers to this device have silently truncated more than once while reporting success.

Quantization and measured accuracy

All graphs are W8A16 (per-channel 8-bit weights, 16-bit activations) except the context adapter, which is FP16. Deploy SNR is measured on device against the fp32 reference, per module:

module	measured	paper target
DistilT5	49.04 dB	—
VAE encoder	41.60 dB	40
VAE decoder	34.27 dB	35
MMDiT stage 0	39.67 dB	29
MMDiT stage 1	37.80 dB	22
MMDiT stage 2	33.89 dB	24
SSD-1B UNet	32.51 dB	—
QuickSRNet	not yet measured	48

QuickSRNet here is W8A16 + CLE. The paper uses W8A16 + AdaRound and credits AdaRound with "7+ dB SQNR" on this module, so expect it to land below 48 dB.

Measured latency (S25 Ultra, on device)

Prompt -> 49-frame video: 23.5-26.9 s (measured before the *fs rebuild). Prompt -> single 640x1024 image: 2.1-2.5 s warm, ~5 s on the first tap of a cold app. Peak app RSS 238-268 MB (binaries are mmap'd, never heap-copied).

Usage

The app fetches each file from <baseUrl>/<name>_v79.bin and places it in its external files dir. For this repo:

https://huggingface.co/AbrahamPJ/neodragon-npu-s25u/resolve/main

This repo is private; the download path sends an Authorization: Bearer <hf_token> header. Use a fine-grained, read-only token scoped to this repo.

Provenance and license

Converted from Qualcomm-AI-Research/Neodragon, which is released under BSD-3-Clause-Clear. That license governs these derived artefacts, and its terms — including the patent clause — carry over. Original work and weights are Qualcomm's; this repo contains only a device-specific recompilation.

Paper: Neodragon, arXiv:2511.06055.

Conversion toolchain: QAIRT SDK 2.49.0.260730 (qnn-onnx-converter → qnn-context-binary-generator). The QAIRT SDK itself is not redistributed here.

Port and conversion work: T2V_NPU.

AbrahamPJ/neodragon-npu-s25u