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mj-kang/GLM-5.3-EXL3-3.0bpw-TP3
GLM-5.3-EXL3-3.0bpw-TP3 is a text generation model from mj-kang. Use it when you need the model to write or continue text. The card lists the license as other.
This is an EXL3/TR3 weight-quantized version of the full GLM-5.3 BF16 checkpoint, not GLM-5.3 Flash. It is not a fine-tune; no additional language-model fine-tuning was performed. It retains all 256 routed experts and…
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Updated Sep 10, 2026
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From the Hugging Face model README
This is an EXL3/TR3 weight-quantized version of the full GLM-5.3 BF16 checkpoint, not GLM-5.3 Flash. It is not a fine-tune; no additional language-model fine-tuning was performed. It retains all 256 routed experts and official top-8 routing, including the MTP layer. The named bpw is the routed-expert quantization target, not the whole-checkpoint average; passthrough tensors remain at source precision.
Geometry is rotating uneven 768/640/640 with no expert-channel padding. The 768-wide owner rotates across normal MoE layers; MTP layer 78 uses rank 2. K3 uses three-bit routed experts; K2.75 mixes 64 two-bit and 192 three-bit experts per routed layer. These are the original sealed versions, not the rejected scale/re-encoding experiments.
This is NOT a stock Transformers, standard vLLM, llama.cpp/GGUF or drop-in ExLlama checkpoint. Use the custom loader, rank-pack preparation, pinned runtime dependencies and safety gates in the reproduction repository. The runtime image/compiled extension are not included here; the source project is an existing-homelab reproduction bundle, not a clean-machine installer.
The sealed checkpoint has more than 19,000 files at its root. To respect Hub folder limits, this repository puts the unchanged original files under checkpoint/part-NNNN/, at most 512 files per part. The original index and manifests are intentionally unchanged and become usable after restoration. TRANSPORT_MANIFEST.json records the exact mapping, byte sizes and SHA256 hashes. The source metadata is also preserved, including its original README and license.
Download the complete repository, then run:
hf download mj-kang/GLM-5.3-EXL3-3.0bpw-TP3 --local-dir ./downloaded-model
python3 ./downloaded-model/restore_checkpoint.py /absolute/path/to/restored-checkpoint --verify
The default restoration links files without copying hundreds of gigabytes. Keep the downloaded snapshot/cache. Use --copy only if you want an independent copy and have enough space. --verify reads every file to validate SHA256; it can take substantial time. Never point restoration at an existing populated directory.
The recorded four-window teacher comparison reports KLD 0.0339743205 nats and top-1 agreement 93.6004%. These are limited calibration-window measurements, not a broad intelligence benchmark, not a percentage of information retained, and not comparable to unrelated GGUF evaluations without matched protocols. See the source repository for runtime/evaluation details and repeatability limits.
The 13.06 tok/s and final 32K/MTP3 qualification in the linked project belong to K2.75, not this K3 checkpoint. Do not attribute those speed or memory results to K3.
304b8051cfb2b260b61ce0cbe330e02a98e73639.GLM-5.3-EXL3-TR3-3.0bpw-TP3-K3-rotating-uneven-v1-assembled-20260906T034145Z.de425ecadfba3b1fa7f60a500c9e156622830454ffad809a1f559dde020f2999.1ea4a0c11d6046060cb713f140a3605b8c50cb7260cea038114ceda6de4b1898.UPLOAD_COMPLETE.json.Original model licensing is preserved in LICENSE. This repository does not replace that license with MIT or Apache. Quantized weight bytes are unchanged from the sealed NAS checkpoint.