What are the hardware requirements for GLM 4.7 REAP 50?

GLM 4.7 REAP 50 requires approximately 219.9 GB of VRAM and supports a context window of 198K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed GLM 4.7 REAP 50 and how large is it?

GLM 4.7 REAP 50 is developed by 0xSero, a model with 184.8b 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 4.7 REAP 50?

GLM 4.7 REAP 50 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

GLM 4.7 REAP 50 by 0xSero — VRAM 219.9GB, 198K context

Name: GLM 4.7 REAP 50
Author: 0xSero

GLM 4.7 REAP 50 is an open-source language model by 0xSero. Features: 184.8b LLM, VRAM: 219.9GB, Context: 198K, License: apache-2.0, LLM Explorer Score: 0.22.

Arxiv:2510.13999 Agentic Cerebras Code Compression Conversational En Endpoints compatible Function-calling Glm Glm4 Glm4 moe Moe Pruning Reap Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/0xSero/GLM-4.7-REAP-50

GLM 4.7 REAP 50 Parameters and Internals

LLM Name	GLM 4.7 REAP 50
Repository 🤗	https://huggingface.co/0xSero/GLM-4.7-REAP-50
Base Model(s)	zai/glm-4.7 zai/glm-4.7
Model Size	184.8b
Required VRAM	219.9 GB
Updated	2026-05-22
Maintainer	0xSero
Model Type	glm4_moe
Model Files	5.0 GB: 1-of-75 5.0 GB: 2-of-75 5.0 GB: 3-of-75 4.9 GB: 4-of-75 5.0 GB: 5-of-75 5.0 GB: 6-of-75 5.0 GB: 7-of-75 5.0 GB: 8-of-75 5.0 GB: 9-of-75 5.0 GB: 10-of-75 5.0 GB: 11-of-75 5.0 GB: 12-of-75 5.0 GB: 13-of-75 5.0 GB: 14-of-75 5.0 GB: 15-of-75 5.0 GB: 16-of-75 5.0 GB: 17-of-75 5.0 GB: 18-of-75 5.0 GB: 19-of-75 5.0 GB: 20-of-75 5.0 GB: 21-of-75 5.0 GB: 22-of-75 5.0 GB: 23-of-75 5.0 GB: 24-of-75 5.0 GB: 25-of-75 5.0 GB: 26-of-75 5.0 GB: 27-of-75 5.0 GB: 28-of-75 5.0 GB: 29-of-75 5.0 GB: 30-of-75 5.0 GB: 31-of-75 5.0 GB: 32-of-75 5.0 GB: 33-of-75 5.0 GB: 34-of-75 5.0 GB: 35-of-75 5.0 GB: 36-of-75 5.0 GB: 37-of-75 5.0 GB: 38-of-75 5.0 GB: 39-of-75 5.0 GB: 40-of-75 5.0 GB: 41-of-75 5.0 GB: 42-of-75 5.0 GB: 43-of-75 5.0 GB: 44-of-75
Supported Languages	en
Model Architecture	Glm4MoeForCausalLM
License	apache-2.0
Context Length	202752
Model Max Length	202752
Transformers Version	4.57.3
Vocabulary Size	151552

Rank the GLM 4.7 REAP 50 capabilities

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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 4.7 REAP 50

Best Alternatives	Context / RAM	Downloads	Likes
GLM 4.7 REAP 50 Mixed 3 4 Bits	198K / 84.8 GB	264	3

Note: green Score (e.g. "73.2") means that the model is better than 0xSero/GLM-4.7-REAP-50.