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llama.cpp fixes qwen2vl model output errors

By PulseAugur Editorial · [1 sources] ·

The llama.cpp project has released an update (b12385) that addresses an issue with the qwen2vl model. Previously, the model produced incorrect outputs due to FFN weight scales not being applied, leading to high perplexity on CUDA and NaN on CPU. This fix ensures the scales are correctly passed to build_ffn, similar to how the Qwen2 model handles them. AI

IMPACT Ensures correct model behavior and performance for qwen2vl within the llama.cpp framework.

RANK_REASON This is a bug fix release for a specific model within the llama.cpp project, not a new model release or significant research.

Read on llama.cpp — Releases →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

llama.cpp fixes qwen2vl model output errors

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36 / 100
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Tool
This is a bug fix release for a specific model within the llama.cpp project, not a new model release or significant research.
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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model release, infra
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High
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Breaking (< 6h)
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COVERAGE [1]

  1. llama.cpp — Releases TIER_1 English(EN) · am17an ·

    b12385: qwen2vl : apply FFN weight scales (#32241)

    <p>The qwen2vl graph passed NULL for the ffn_up/gate/down scales, so the<br /> per-tensor NVFP4 scales loaded by the generic pass were never applied<br /> and the model produced garbage (PPL ~1e6 on CUDA, NaN on CPU).</p> <p>Pass the scales to build_ffn like qwen2 does.</p> <p>Fi…

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