What are the hardware requirements for WesleyGPT Think?

WesleyGPT Think requires approximately 0.8 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed WesleyGPT Think and how large is it?

WesleyGPT Think is developed by Wasue, a model with 400b 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 WesleyGPT Think?

WesleyGPT Think is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

WesleyGPT Think by Wasue — VRAM 0.8GB

Name: WesleyGPT Think
Author: Wasue

WesleyGPT Think is an open-source language model by Wasue. Features: 400b LLM, VRAM: 0.8GB, License: cc-by-nc-4.0, LLM Explorer Score: 0.3.

Base model:finetune:wasue/wesl... Base model:wasue/wesleygpt-bas... Consumer-gpu Dataset:cais/mmlu Dataset:huggingfacetb/smol-smo... Dataset:karpathy/climbmix-400b... Dataset:meta-math/metamathqa Dataset:openai/gsm8k En Nanochat Reasoning Region:us Safetensors Small-language-model Trained-from-scratch

Model Card on HF 🤗: https://huggingface.co/Wasue/WesleyGPT-Think

WesleyGPT Think Parameters and Internals

LLM Name	WesleyGPT Think
Repository 🤗	https://huggingface.co/Wasue/WesleyGPT-Think
Base Model(s)	WesleyGPT Base Wasue/WesleyGPT-Base
Model Size	400b
Required VRAM	0.8 GB
Updated	2026-09-29
Maintainer	Wasue
Model Files	0.8 GB
Supported Languages	en
License	cc-by-nc-4.0

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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