What are the hardware requirements for Yi 1.5 6B Chat GGUF?

Yi 1.5 6B Chat GGUF requires approximately 2.3 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Yi 1.5 6B Chat GGUF and how large is it?

Yi 1.5 6B Chat GGUF is developed by MaziyarPanahi, a model with 6b 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 Yi 1.5 6B Chat GGUF?

Yi 1.5 6B Chat GGUF is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Yi 1.5 6B Chat GGUF by MaziyarPanahi — VRAM 2.3GB

Name: Yi 1.5 6B Chat GGUF
Author: MaziyarPanahi

Yi 1.5 6B Chat GGUF is an open-source language model by MaziyarPanahi. Features: 6b LLM, VRAM: 2.3GB, Quantized, LLM Explorer Score: 0.19.

Arxiv:2403.04652 2-bit 3-bit 4-bit 5-bit 6-bit 8-bit Autotrain compatible Base model:01-ai/yi-1.5-6b-cha... Base model:quantized:01-ai/yi-... Conversational Endpoints compatible Gguf Llama Mistral Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/MaziyarPanahi/Yi-1.5-6B-Chat-GGUF

Yi 1.5 6B Chat GGUF Parameters and Internals

Model Type

text-generation, quantized

Additional Notes

Contains GGUF format model files for 01-ai/Yi-1.5-6B-Chat.

LLM Name	Yi 1.5 6B Chat GGUF
Repository 🤗	https://huggingface.co/MaziyarPanahi/Yi-1.5-6B-Chat-GGUF
Model Name	Yi-1.5-6B-Chat-GGUF
Model Creator	01-ai
Base Model(s)	01-ai/Yi-1.5-6B-Chat 01-ai/Yi-1.5-6B-Chat
Model Size	6b
Required VRAM	2.3 GB
Updated	2026-08-06
Maintainer	MaziyarPanahi
Model Type	mistral
Model Files	2.3 GB 3.2 GB 3.0 GB 2.7 GB 3.7 GB 3.5 GB 4.3 GB 4.2 GB 5.0 GB
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	AutoModel

Rank the Yi 1.5 6B Chat GGUF 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

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