Developers download quantized large language models (LLMs) from public registries to run them locally. None of the registries we examined documented functional testing of their files. We tested all 30
Quantized small language model files in public registries can be non-functional due to uncalibrated quantization recipes, and screening plus calibration is recommended before release.
Developers download quantized large language models (LLMs) from public registries to run them locally. None of the registries we examined documented functional testing of their files. We tested all 305 eligible code-capable GGUF tags (the llama.cpp format) across 15 model lines in the official Ollama library, plus 22 popular Hugging Face community files. A 15-task code screen identified suspects, which we retested on all 164 HumanEval+ tasks. Seven official tags (2.3%) solved at most six of them. All were low-bit quantizations of models with at most four billion parameters. We rebuilt five suspect files from the original weights. All five registry files matched our uncalibrated rebuilds…
Summary and abstract excerpt via Hugging Face Papers ↗ · arXiv.
Broken on Arrival: Non-Functional Quantized LLM Artifacts in Public Model Registries and How to Catch Them was first seen on Hugging Face · Daily papers on Nov 2, 2026. Since then it has appeared in 5 checks on 2 different days. Its best position was #25 of 30, reached on Nov 2, 19:28 UTC. It dropped off the list after Nov 3, 01:28 UTC.
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Not at the moment. It was last on the list on Nov 3, 01:28 UTC, after 2 days of trending.
#25 on Hugging Face · Daily papers, on Nov 2, 19:28 UTC. Trendoday checks this list every 120 minutes.
It was first seen on Nov 2, 2026 and has been on the list on 2 days (5 checks) since.