Terra3312/GLM-5.3-Flash-EXL3-4bpw-MUL1
GLM-5.3-Flash EXL3 4 bpw MUL1
An EXL3 quantization of zai-org/GLM-5.3-Flash, created with the mul1 codebook for ExLlamaV3.
This checkpoint is intended for efficient local inference with ExLlamaV3, with particular interest in single-stream decode performance on large MoE models.
The main language-model weights use 4.0 bpw. The vision component and lm_head use 6 bpw.
Quantization details
- Base model:
zai-org/GLM-5.3-Flash - Format: EXL3
- Main language-model bitrate: 4.0 bpw
- Vision bitrate: 6 bpw
lm_headbitrate: 6 bpw- MTP bitrate: 4 bpw
- Codebook:
mul1 - EXL3 metadata version:
1.4.4 - Output scales:
always - Quantizer: ExLlamaV3
- Calibration metadata:
rows=250,cols=2048
The calibration dataset, prompts, random seed, and exact ExLlamaV3 commit were not recorded in the checkpoint.
The checkpoint also preserves the original model-side quantization metadata:
- Original format: FP8
- FP8 format:
e4m3 - Activation scheme: dynamic
- Weight block size:
[128, 128]
Why MUL1?
The mul1 codebook is supported by ExLlamaV3's fused INT8-activation GEMV path.
For supported tensors, GPUs, and tensor shapes, this path may improve single-stream decode performance. Actual performance depends on GPU architecture, context length, tensor parallel configuration, runtime version, and workload.
To test the INT8 GEMV path:
EXL3_INT8_GEMV=2To disable it:
EXL3_INT8_GEMV=0The current ExLlamaV3 runtime uses the INT8 GEMV path by default where supported. See the ExLlamaV3 environment-variable documentation.
Usage
Use a recent ExLlamaV3 build with GLM-5.3-Flash and mul1 support.
Load the complete repository directory, including:
config.jsonquantization_config.jsonmodel.safetensors.index.json- all
model-*.safetensorsfiles - tokenizer and processor files
This checkpoint is intended for ExLlamaV3-compatible local inference and is not an official release from Z.ai or ExLlamaV3.
Credits
- Original model: Z.ai — GLM-5.3-Flash
- Quantization and runtime: ExLlamaV3
License
The original GLM-5.3-Flash model is released under the MIT License. Please refer to the included LICENSE file and the original model repository for the applicable terms.
