AI가 움직이고 미래가 업데이트됩니다.GLM-5.3-Flash-NVFP4
NVFP4 (4-bit float, group size 16) quantization of `zai-org/GLM-5.3-Flash`, covering the routed experts of **every** MoE layer — including layer 45, the multi-token-prediction (MTP) layer — in a **single, uniform** scheme. **No calibration data is used in this quantization step**, and none is needed: the scheme quantizes each group of 16 weights with a scale derived from those 16 values (`memoryless_minmax`), so there is no forward pass for calibration data to inform. The checkpoint contains no activation-scale tensors and declares `input_activations: null`. `num_hidden_layers: 45` plus `num_nextn_predict_layers: 1` puts the MTP layer at index **45**, and it is not a small head: 288 routed experts, ~7.25 B parameters, its own DSA attention and `eh_proj`/`enorm`/`hnorm` plumbing. Keeping it in the same scheme as every other expert layer means the checkpoint has one expert layout throughout — 37,152 packed expert tensors (43 × 288 × 3).
번역 준비 중입니다. 원문을 표시합니다.
NVFP4 (4-bit float, group size 16) quantization of `zai-org/GLM-5.3-Flash`, covering the routed experts of **every** MoE layer — including layer 45, the multi-token-prediction (MTP) layer — in a **single, uniform** scheme. **No calibration data is used in this quantization step**, and none is needed: the scheme quantizes each group of 16 weights with a scale derived from those 16 values (`memoryless_minmax`), so there is no forward pass for calibration data to inform. The checkpoint contains no activation-scale tensors and declares `input_activations: null`. `num_hidden_layers: 45` plus `num_nextn_predict_layers: 1` puts the MTP layer at index **45**, and it is not a small head: 288 routed experts, ~7.25 B parameters, its own DSA attention and `eh_proj`/`enorm`/`hnorm` plumbing. Keeping it in the same scheme as every other expert layer means the checkpoint has one expert layout throughout — 37,152 packed expert tensors (43 × 288 × 3).