What are the hardware requirements for GLM 5.3 DERISKED BF16?

GLM 5.3 DERISKED BF16 requires approximately 428 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 DERISKED BF16 and how large is it?

GLM 5.3 DERISKED BF16 is developed by Blackfrost-Research, 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 DERISKED BF16?

GLM 5.3 DERISKED BF16 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

GLM 5.3 DERISKED BF16 by Blackfrost-Research — VRAM 428GB, 1024K context

Name: GLM 5.3 DERISKED BF16
Author: Blackfrost-Research

GLM 5.3 DERISKED BF16 is an open-source language model by Blackfrost-Research. Features: 753.3b LLM, VRAM: 428GB, Context: 1024K, License: other, MoE, LLM Explorer Score: 0.29.

Base model:finetune:zai-org/gl... Base model:zai-org/glm-5.3-bf1... Bf16 Conversational De-risked En Endpoints compatible Enterprise Glm Glm-5.3 Glm moe dsa Mixture-of-experts Moe Red-teaming Region:us Safetensors Security-research Sharded Tensorflow Zh

Model Card on HF 🤗: https://huggingface.co/Blackfrost-Research/GLM-5.3-DERISKED-BF16

GLM 5.3 DERISKED BF16 Parameters and Internals

LLM Name	GLM 5.3 DERISKED BF16
Repository 🤗	https://huggingface.co/Blackfrost-Research/GLM-5.3-DERISKED-BF16
Base Model(s)	zai-org/GLM-5.3-BF16 zai-org/GLM-5.3-BF16
Model Size	753.3b
Required VRAM	428 GB
Updated	2026-10-17
Maintainer	Blackfrost-Research
Model Type	glm_moe_dsa
Model Files	12.9 GB: 1-of-158 6.4 GB: 2-of-158 4.8 GB: 3-of-158 12.9 GB: 4-of-158 6.4 GB: 5-of-158 12.9 GB: 6-of-158 6.4 GB: 7-of-158 12.9 GB: 8-of-158 6.4 GB: 9-of-158 12.9 GB: 10-of-158 6.4 GB: 11-of-158 12.9 GB: 12-of-158 6.4 GB: 13-of-158 12.9 GB: 14-of-158 6.4 GB: 15-of-158 12.9 GB: 16-of-158 6.4 GB: 17-of-158 12.9 GB: 18-of-158 6.4 GB: 19-of-158 12.9 GB: 20-of-158 6.4 GB: 21-of-158 12.9 GB: 22-of-158 6.4 GB: 23-of-158 12.9 GB: 24-of-158 6.4 GB: 25-of-158 12.9 GB: 26-of-158 6.4 GB: 27-of-158 5.0 GB: 28-of-158 12.9 GB: 29-of-158 6.4 GB: 30-of-158 12.9 GB: 31-of-158 6.4 GB: 32-of-158 12.9 GB: 33-of-158 6.4 GB: 34-of-158 12.9 GB: 35-of-158 6.4 GB: 36-of-158 12.9 GB: 37-of-158 6.4 GB: 38-of-158 12.9 GB: 39-of-158 6.4 GB: 40-of-158 12.9 GB: 41-of-158 6.4 GB: 42-of-158 12.9 GB: 43-of-158 6.4 GB: 44-of-158 12.9 GB: 45-of-158
Supported Languages	en zh
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 DERISKED BF16 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 DERISKED BF16

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
GLM 5.3 BF16	1024K / 237.4 GB	482	24
GLM 5.3 CYBERSECURITY FP8	1024K / 112.6 GB	227	29
Macaron V1.1	1024K / 221.2 GB	202	8
GLM 5.3 MXFP4	1024K / 132.2 GB	649	1
GLM 5.2	1024K / 237.4 GB	1671	26

Note: green Score (e.g. "73.2") means that the model is better than Blackfrost-Research/GLM-5.3-DERISKED-BF16.