{
  "schema": "tokforge-sdxl-qnn-npu/manifest@1",
  "model": "realvisxl-v4.0-lightning",
  "variant": "fp16-encoders + TAESDXL",
  "scheduler": "EulerDiscrete",
  "native_steps": 6,
  "license": "openrail++",
  "license_note": "RealVisXL V4.0 Lightning is released under the CreativeML OpenRAIL++-M license. Commercial use permitted; no revenue cap (unlike the prior SDXL-Turbo Stability AI Community License). Use-based restrictions per the OpenRAIL++ schedule apply.",
  "generated": "2026-06-06T00:00:00Z",
  "repo": "darkmaniac7/TokForge-SDXL-QNN-NPU",
  "notes": [
    "vc410: 'Faithful' NPU tier = RealVisXL-v4.0-Lightning, replacing cursed base SDXL-Turbo (few-step distillation -> fused heads / doubled bodies). Bin-only swap on the SAME W8A16 NPU recipe + IO contract; the driver default scheduler flips EulerAncestral -> EulerDiscrete (Lightning is distilled for deterministic few-step Euler) and native steps 4 -> 6.",
    "App reads the device Hexagon arch (dsp_arch) and picks the matching native set. Four native sets ship: v73/v75/v79/v81. Forward-compat still applies (a lower-arch bin runs on a higher-arch DSP) as a fallback.",
    "source=ours: clean-room RealVisXL -> W8A16 -> QAIRT 2.40 conversion, drop-in for our libsdxl_qnn_driver (graph name 'model', host combined-emb input).",
    "verified=true = run on real silicon and confirmed coherent (no body-horror). V75 (Lenovo .69) + V81 (RedMagic .82) device-verified. v73/v79 offline-validated, awaiting handsets.",
    "The 4 per-arch bins (unet/text_encoder_1_fp16/text_encoder_2_fp16/sdxl_emb_mlp) are the only RealVisXL swap; taesdxl_decoder.mnn (universal SDXL tiny-VAE) + the dual CLIP tokenizers + config are checkpoint-agnostic and byte-identical to the prior set."
  ],
  "arch_to_socs": {
    "73": {
      "name": "Hexagon V73",
      "socs": [
        "SM8550 (Snapdragon 8 Gen 2)",
        "SM8635 (8s Gen 3)",
        "SM7475 (7+ Gen 3)"
      ]
    },
    "75": {
      "name": "Hexagon V75",
      "socs": [
        "SM8650 (Snapdragon 8 Gen 3)",
        "SM7675 (7 Gen 4)"
      ]
    },
    "79": {
      "name": "Hexagon V79",
      "socs": [
        "SM8750 (Snapdragon 8 Elite)",
        "SM8750-AB (8 Elite for Galaxy)"
      ]
    },
    "81": {
      "name": "Hexagon V81",
      "socs": [
        "SM8850 (Snapdragon 8 Elite Gen 5)"
      ]
    }
  },
  "io_contracts": {
    "ours-sdxl-emb": {
      "graph_name": "model",
      "unet_inputs": {
        "sample": "[1,4,128,128] UFIXED16 (NCHW, raw scheduler latent)",
        "emb": "[1,1280] UFIXED16 host combined-emb = time_embedding(time_proj(t)) + add_embedding(cat(pooled, add_time_proj(time_ids))); computed host-side via sdxl_emb_mlp.bin",
        "text_embedding": "[1,77,2048] UFIXED16 = concat CLIP-L last_hidden[1,77,768] ++ bigG last_hidden[1,77,1280]"
      },
      "unet_output": "output [1,4,128,128] UFIXED16",
      "text_encoder_1": "CLIP-L: in input_ids INT32 [1,77] -> out last_hidden [1,77,768] (penultimate, hidden -2)",
      "text_encoder_2": "OpenCLIP-bigG (+projection): in input_ids INT32 [1,77] -> out last_hidden [1,77,1280] + pooled [1,1280]",
      "vae": "TAESDXL CPU tiny-VAE (taesdxl_decoder.mnn), in latent [1,4,128,128] -> out [1,3,1024,1024]; CPU MNN path only (SDXL_VAE_BACKEND=cpu)",
      "scheduler": "EulerDiscrete (deterministic, sigma_up=0), trailing spacing, epsilon prediction, 6 steps native, guidance_scale 0 (NO CFG -> ONE UNet pass per step)",
      "vae_scaling_factor": 0.13025,
      "resolution": 1024,
      "driver": "libsdxl_qnn_driver.so (#51 ImageGenerationSdxlNpuCliHelper); flags --text_encoder_1/--text_encoder_2/--unet/--vae_mnn/--emb_mlp/--vocab_1/--merges_1/--vocab_2/--merges_2/--backend/--system_library; env SDXL_VAE_BACKEND=cpu"
    }
  },
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      "soc_model": 43,
      "qairt_runtime_required": "2.40",
      "skel": "libQnnHtpV73Skel.so",
      "io_contract": "ours-sdxl-emb",
      "verified": false,
      "verify_note": "Native v73 bins produced from the same arch-agnostic W8A16 DLC as the device-verified V75/V81 sets (only dsp_arch/soc_model differ); offline-validated, awaiting a handset.",
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      "soc_model": 57,
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      "skel": "libQnnHtpV75Skel.so",
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  "model_id": "image-sdxl-qnn-npu",
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}