What are the hardware requirements for GLM 5.3 MXFP4 AutoRound?

GLM 5.3 MXFP4 AutoRound requires approximately 126.4 GB of VRAM and supports a context window of 1024K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed GLM 5.3 MXFP4 AutoRound and how large is it?

GLM 5.3 MXFP4 AutoRound is developed by intel-ai, a model with 753.3b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate GLM 5.3 MXFP4 AutoRound?

GLM 5.3 MXFP4 AutoRound is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

GLM 5.3 MXFP4 AutoRound by intel-ai — VRAM 126.4GB, 1024K context

Name: GLM 5.3 MXFP4 AutoRound
Author: intel-ai

GLM 5.3 MXFP4 AutoRound is an open-source language model by intel-ai. Features: 753.3b LLM, VRAM: 126.4GB, Context: 1024K, License: other, MoE.

Arxiv:2309.05516 8-bit Auto-round Base model:quantized:zai-org/g... Base model:zai-org/glm-5.3 Compressed-tensors Conversational Endpoints compatible Eval-results Glm moe dsa Moe Mxfp4 Region:us Safetensors Sharded Tensorflow Vllm

Model Card on HF 🤗: https://huggingface.co/intel-ai/GLM-5.3-MXFP4-AutoRound

GLM 5.3 MXFP4 AutoRound Parameters and Internals

LLM Name	GLM 5.3 MXFP4 AutoRound
Repository 🤗	https://huggingface.co/intel-ai/GLM-5.3-MXFP4-AutoRound
Base Model(s)	zai-org/GLM-5.3 zai-org/GLM-5.3
Model Size	753.3b
Required VRAM	126.4 GB
Updated	2026-11-06
Maintainer	intel-ai
Model Type	glm_moe_dsa
Model Files	4.6 GB: 1-of-141 2.9 GB: 2-of-141 2.9 GB: 3-of-141 2.9 GB: 4-of-141 2.9 GB: 5-of-141 2.9 GB: 6-of-141 2.9 GB: 7-of-141 2.9 GB: 8-of-141 2.9 GB: 9-of-141 2.9 GB: 10-of-141 2.9 GB: 11-of-141 2.9 GB: 12-of-141 2.9 GB: 13-of-141 2.9 GB: 14-of-141 2.9 GB: 15-of-141 2.9 GB: 16-of-141 2.9 GB: 17-of-141 2.9 GB: 18-of-141 2.9 GB: 19-of-141 2.9 GB: 20-of-141 2.9 GB: 21-of-141 2.9 GB: 22-of-141 2.9 GB: 23-of-141 2.9 GB: 24-of-141 2.9 GB: 25-of-141 2.9 GB: 26-of-141 2.9 GB: 27-of-141 2.9 GB: 28-of-141 2.9 GB: 29-of-141 2.9 GB: 30-of-141 2.9 GB: 31-of-141 2.9 GB: 32-of-141 2.9 GB: 33-of-141 2.9 GB: 34-of-141 2.9 GB: 35-of-141 2.9 GB: 36-of-141 2.9 GB: 37-of-141 2.9 GB: 38-of-141 2.9 GB: 39-of-141 2.9 GB: 40-of-141 2.9 GB: 41-of-141 2.9 GB: 42-of-141 2.9 GB: 43-of-141
Model Architecture	GlmMoeDsaForCausalLM
License	other
Context Length	1048576
Model Max Length	1048576
Transformers Version	5.15.0
Vocabulary Size	154880

Rank the GLM 5.3 MXFP4 AutoRound capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Best Alternatives to GLM 5.3 MXFP4 AutoRound

Best Alternatives	Context / RAM	Downloads	Likes
GLM 5.3	1024K / 232.2 GB	8804	1255
GLM 5.2	1024K / 232 GB	2391730	4875
Atria Dawn Preview	1024K / 183.2 GB	1688	248
...3 F.U AnthraClaud Edition BF16	1024K / 428 GB	1259	60
GLM 5.3 NVFP4	1024K / 465.2 GB	1973	3
ToolSpace 744B A40B	1024K / 184.2 GB	186	1
Lucia III	1024K / 234.9 GB	148	1
GLM 5.3 DERISKED BF16	1024K / 428 GB	164	61
GLM 5.3 BF16	1024K / 237.4 GB	482	24
GLM 5.3	1024K / 232.2 GB	50	1

Note: green Score (e.g. "73.2") means that the model is better than intel-ai/GLM-5.3-MXFP4-AutoRound.