What are the hardware requirements for Yi 1.5 34B Chat GGUF?

Yi 1.5 34B Chat GGUF requires approximately 12.8 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Yi 1.5 34B Chat GGUF and how large is it?

Yi 1.5 34B Chat GGUF is developed by MaziyarPanahi, a model with 34b 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 34B Chat GGUF?

Yi 1.5 34B 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 34B Chat GGUF by MaziyarPanahi — VRAM 12.8GB

Name: Yi 1.5 34B Chat GGUF
Author: MaziyarPanahi

Yi 1.5 34B Chat GGUF is an open-source language model by MaziyarPanahi. Features: 34b LLM, VRAM: 12.8GB, Quantized, LLM Explorer Score: 0.12.

Arxiv:2403.04652 2-bit 3-bit 4-bit 5-bit 6-bit 8-bit Autotrain compatible Base model:01-ai/yi-1.5-34b-ch... 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-1.5-34B-Chat-GGUF

Yi 1.5 34B Chat GGUF Parameters and Internals

Model Type

text-generation

Additional Notes

GGUF is a new format introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp.

LLM Name	Yi 1.5 34B Chat GGUF
Repository 🤗	https://huggingface.co/MaziyarPanahi/Yi-1.5-34B-Chat-GGUF
Model Name	Yi-1.5-34B-Chat-GGUF
Model Creator	01-ai
Base Model(s)	01-ai/Yi-1.5-34B-Chat 01-ai/Yi-1.5-34B-Chat
Model Size	34b
Required VRAM	12.8 GB
Updated	2026-06-15
Maintainer	MaziyarPanahi
Model Type	mistral
Model Files	12.8 GB 18.1 GB 16.7 GB 15.0 GB 20.7 GB 19.6 GB 24.3 GB 23.7 GB 28.2 GB
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	AutoModel

Rank the Yi 1.5 34B Chat GGUF 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

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StructLM 34B GGUF	0K / 12.5 GB	196	2
CodeLlama 34B Python Hf GGUF	0K / 12.5 GB	514	1
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Note: green Score (e.g. "73.2") means that the model is better than MaziyarPanahi/Yi-1.5-34B-Chat-GGUF.