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README.md

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+---
+base_model: zai-org/GLM-5
+library_name: mlx
+license: mit
+tags:
+- mlx
+- safetensors
+- glm_moe_dsa
+- conversational
+- text-generation
+- mxfp4
+- quantized
+language:
+- en
+- zh
+---
+
+# mlx-community/GLM-5-MXFP4-Q8
+
+This model was converted to MLX format from [`zai-org/GLM-5`](https://huggingface.co/zai-org/GLM-5) using a custom MXFP4-Q8 quantization scheme.
+
+GLM-5 is a 744B parameter (40B active) Mixture-of-Experts model developed by Z.ai, targeting complex systems engineering and long-horizon agentic tasks. It uses Multi-Head Latent Attention (MLA) with 47 transformer layers, 64 routed experts (4 active per token), and 1 shared expert.
+
+## Quantization
+
+This model uses a mixed-precision quantization.
+
+| Component | Mode | Bits | Group Size |
+|---|---|---|---|
+| Expert weights (switch_mlp) | MXFP4 | 4 | 32 |
+| Attention, embeddings, shared expert, dense MLP, lm_head | Affine | 8 | 64 |
+
+## Use with mlx-lm
+
+```bash
+pip install mlx-lm
+```
+
+```python
+from mlx_lm import load, generate
+
+model, tokenizer = load("mlx-community/GLM-5-MXFP4-Q8")
+
+prompt = "hello"
+
+if tokenizer.chat_template is not None:
+    messages = [{"role": "user", "content": prompt}]
+    prompt = tokenizer.apply_chat_template(
+        messages, add_generation_prompt=True
+    )
+
+response = generate(model, tokenizer, prompt=prompt, verbose=True)
+```