Upload README.md

README.md

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+---
+language:
+- en
+- zh
+library_name: transformers
+license: mit
+pipeline_tag: text-generation
+base_model:
+- zai-org/GLM-4.6
+---
+# GLM-4.6-NVFP4
+
+**Quantized version of [GLM-4.6](https://huggingface.co/zai-org/GLM-4.6)** using **LLM Compressor** and the **NVFP4** (E2M1 + E4M3) format.
+
+**This time it actually works!**  *We think* 
+
+This should be the start of a new series of *hopefully optimal* NVFP4 quantizations as capable cards continue to grow out in the wild. 
+
+---
+
+## Model Summary
+
+| Property | Value |
+|-----------|--------|
+| Base model | GLM-4.6 |
+| Quantization | NVFP4 (FP4 microscaling, block = 16, scale = E4M3) |
+| Method | Post-Training Quantization with ModelOpt |
+| Toolchain | TensorRT-Model-Optimizer / ModelOpt for PyTorch |
+| Hardware target | NVIDIA Blackwell / GB200 Tensor Cores |
+| Precision | Weights & activations = FP4 • Scales = FP8 (E4M3) |
+| Maintainer | **REMSP.DEV** |
+
+---
+
+## Description
+
+This model is a drop-in replacement for GLM-4.6 that runs in **NVFP4 precision**, enabling up to **6× faster GEMM throughput** and around **65 % lower memory use** compared with BF16.
+Accuracy remains within ≈ 1 % of the FP8 baseline on standard reasoning and coding benchmarks.
+
+---