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    "command": "python convert_lfm25_vl3b.py ../src_models/lfm25-vl-450m out_vl450m_fp2 --fp && python quantize_vl.py out_vl450m_fp2/model.litertlm LFM2.5-VL-450M_int4.litertlm",
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  },
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            "VERBOSE: Replacing 468 out of 543 node(s) with delegate (TfLiteXNNPackDelegate) node, yielding 86 partitions for subgraph 1 (prefill_512).",
            "VERBOSE: Replacing 468 out of 543 node(s) with delegate (TfLiteXNNPackDelegate) node, yielding 86 partitions for subgraph 2 (prefill_256).",
            "VERBOSE: Replacing 468 out of 543 node(s) with delegate (TfLiteXNNPackDelegate) node, yielding 86 partitions for subgraph 3 (prefill_128).",
            "results block: prefill=403.63 decode=99.25 tokens/s"
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        "device": "galaxy-s26",
        "run": {
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          "date": "2026-08-24",
          "decode_tokens_per_s": 103.02,
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            "VERBOSE: Replacing 543 out of 543 node(s) with delegate (LITERT_CL) node, yielding 1 partitions for subgraph 1 (prefill_512).",
            "VERBOSE: Replacing 543 out of 543 node(s) with delegate (LITERT_CL) node, yielding 1 partitions for subgraph 2 (prefill_256).",
            "VERBOSE: Replacing 543 out of 543 node(s) with delegate (LITERT_CL) node, yielding 1 partitions for subgraph 3 (prefill_128).",
            "results block: prefill=2699.59 decode=103.02 tokens/s"
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            "VERBOSE: Replacing 543 out of 543 node(s) with delegate (LITERT_CL) node, yielding 1 partitions for subgraph 1 (prefill_512).",
            "VERBOSE: Replacing 543 out of 543 node(s) with delegate (LITERT_CL) node, yielding 1 partitions for subgraph 2 (prefill_256).",
            "VERBOSE: Replacing 543 out of 543 node(s) with delegate (LITERT_CL) node, yielding 1 partitions for subgraph 3 (prefill_128).",
            "results block: prefill=528.07 decode=33.05 tokens/s"
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  },
  "model": {
    "family": "lfm2_vl",
    "id": "lfm25-vl-450m-int4",
    "license": "lfm-open-license-v1.0",
    "source_url": "https://huggingface.co/LiquidAI/LFM2.5-VL-450M",
    "task": "image-text-to-text"
  },
  "pitfalls": [
    "int4 is the better variant of this model on our gates — 8/8 text and 4/5 image vs the int8's 6/8 and 3/5; on Pixel 8a CPU int4 prefills slower than int8 (blockwise repacking) but decodes ~40% faster — pick by whether prompts or outputs dominate (HF card, measured).",
    "64k vocab (stop ids 7/2, same as the 1.2B text family) — the 3B's 128k pbtext does not transfer; verify generation_config before reusing metadata across sizes (REPRODUCE.md).",
    "Fine-grained shape questions can miss on-device at this scale across all quant levels including an unquantized probe, while the torch reference answers them; conversion exonerated by experiment (vision tflite cosine 1.0000, token-identical streams, geometry probes correct). Treat as a fast small VLM for coarse visual tasks and large-text OCR; the 3B answers all fixtures (RESULTS.md; HF card wording).",
    "Same VLM-bundle mechanics as the siblings: transformers==5.14.1 pin; llm_model_type { lfm2 {} } with bare <image> template; externalized-embedder int8 pass; pack/unpack post-processing (single-tflite tools drop vision sections) (REPRODUCE.md).",
    "Zero-scale fix is a no-op on this checkpoint (0 all-zero blocks, like the 1.2B family); harmless to keep in the pipeline (RESULTS.md).",
    "iPhone GPU blocked (LiteRT-LM#3129) — iOS runs CPU; Android OpenCL delegates fully (543/543)."
  ],
  "schema_version": "1.2"
}
