This is a quantized build of GLM-5.3-Flash-Uncensored-FP8. Only the routed MoE experts are re-quantized; every other tensor is kept exactly as in the FP8 source (FP8 tensors stay FP8, BF16 tensors stay BF16). The model card below this section is the original card of the FP8 checkpoint. Total ~179 GiB (the FP8 source is 306 GiB). Format. compressed-tensors, mixed-precision with two config groups in config.json: - group0 (pack-quantized, targets re:.mlp\.experts\..): the layout llm-compressor writes, per expert projection weightpacked (int32, eight 4-bit values each), weightscale (BF16, one per 32 consecutive input-channel weights) and weightshape. - group1 (float-quantized, targets the…
Open weights
mit
321.3B parameters
1,048,576 tokens
transformers
This is a quantized build of Qwen3.8-Flash-Next-Uncensored (BF16). Only the routed MoE experts are quantized; every other tensor is kept exactly as in the BF16 source. The model card below this section is the original BF16 card. Total ~174 GiB (the BF16 source is ~336 GB). Format. compressed-tensors pack-quantized, the layout llm-compressor writes: per expert projection, weightpacked (int32, eight 4-bit values each), weightscale (BF16, one per 32 consecutive input-channel weights) and weightshape. quantizationconfig in config.json targets re:.mlp\.experts\.. and ignores re:.mtp., re:.visual. and lmhead. Method. Data-free round-to-nearest, no calibration data (no GPTQ / AWQ). Each weight is…
Open weights
apache-2.0
180B parameters
262,144 tokens
transformers
