What are the hardware requirements for GLM 5.3 Flash MXFP4 Mixed CT AutoRound?

GLM 5.3 Flash MXFP4 Mixed CT AutoRound requires approximately 67.4 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

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

GLM 5.3 Flash MXFP4 Mixed CT AutoRound is developed by INCModel3, a model with 321.3b 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 Flash MXFP4 Mixed CT AutoRound?

GLM 5.3 Flash MXFP4 Mixed CT 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 Flash MXFP4 Mixed CT AutoRound by INCModel3 — VRAM 67.4GB

Name: GLM 5.3 Flash MXFP4 Mixed CT AutoRound
Author: INCModel3

GLM 5.3 Flash MXFP4 Mixed CT AutoRound is an open-source language model by INCModel3. Features: 321.3b LLM, VRAM: 67.4GB, License: mit, LLM Explorer Score: 0.31.

Arxiv:2309.05516 8-bit Base model:quantized:zai-org/g... Base model:zai-org/glm-5.3-fla... Compressed-tensors Conversational En Endpoints compatible Glm5 next Image-text-to-text Region:us Safetensors Sharded Tensorflow Zh

Model Card on HF 🤗: https://huggingface.co/INCModel3/GLM-5.3-Flash-MXFP4-Mixed-CT-AutoRound

GLM 5.3 Flash MXFP4 Mixed CT AutoRound Parameters and Internals

LLM Name	GLM 5.3 Flash MXFP4 Mixed CT AutoRound
Repository 🤗	https://huggingface.co/INCModel3/GLM-5.3-Flash-MXFP4-Mixed-CT-AutoRound
Base Model(s)	zai-org/GLM-5.3-Flash zai-org/GLM-5.3-Flash
Model Size	321.3b
Required VRAM	67.4 GB
Updated	2026-09-02
Maintainer	INCModel3
Model Type	glm5_next
Model Files	3.9 GB: 1-of-120 1.4 GB: 2-of-120 1.4 GB: 3-of-120 1.6 GB: 4-of-120 1.4 GB: 5-of-120 1.4 GB: 6-of-120 1.6 GB: 7-of-120 1.4 GB: 8-of-120 1.6 GB: 9-of-120 1.4 GB: 10-of-120 1.4 GB: 11-of-120 1.6 GB: 12-of-120 1.4 GB: 13-of-120 1.4 GB: 14-of-120 1.6 GB: 15-of-120 1.4 GB: 16-of-120 1.4 GB: 17-of-120 1.6 GB: 18-of-120 1.4 GB: 19-of-120 1.5 GB: 20-of-120 1.5 GB: 21-of-120 1.4 GB: 22-of-120 1.6 GB: 23-of-120 1.4 GB: 24-of-120 1.4 GB: 25-of-120 1.6 GB: 26-of-120 1.4 GB: 27-of-120 1.4 GB: 28-of-120 1.9 GB: 29-of-120 1.4 GB: 30-of-120 1.4 GB: 31-of-120 1.6 GB: 32-of-120 1.4 GB: 33-of-120 1.6 GB: 34-of-120 1.4 GB: 35-of-120 1.4 GB: 36-of-120 1.6 GB: 37-of-120 1.4 GB: 38-of-120 1.4 GB: 39-of-120 1.6 GB: 40-of-120 1.4 GB: 41-of-120 1.4 GB: 42-of-120 1.6 GB: 43-of-120 1.4 GB: 44-of-120
Supported Languages	en zh
Model Architecture	Glm5NextForConditionalGeneration
License	mit
Transformers Version	5.16.0

Rank the GLM 5.3 Flash MXFP4 Mixed CT 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
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Data Analysis and Insight Generation
Text Generation
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Code Generation
Multi-Language Support and Translation

Best Alternatives to GLM 5.3 Flash MXFP4 Mixed CT AutoRound

Best Alternatives	Context / RAM	Downloads	Likes
GLM 5.3 Flash	0K / 237.5 GB	34	1289
GLM 5.3 Flash BF16	0K / 237.1 GB	24	38
GLM 5.3 Flash FP8	0K / 237.5 GB	5048	22
GLM 5.3 Flash Nota NVFP4	0K / 21 GB	160	17
GLM 5.3 Flash	0K / 242.5 GB	1034	15
GLM 5.3 Flash DERISKED BF16	0K / 237.1 GB	127	2
...Flash Abliterated Experimental	0K / 471.3 GB	69	3
GLM 5.3 Flash W4A16	0K / 73.1 GB	53	1
Jah 5.0	0K / 237.5 GB	14	1
GLM 5.3 Flash DERISKED BF16	0K / 237.1 GB	0	2

Note: green Score (e.g. "73.2") means that the model is better than INCModel3/GLM-5.3-Flash-MXFP4-Mixed-CT-AutoRound.