What are the hardware requirements for AquilaChat2 34B GGUF?

AquilaChat2 34B GGUF requires approximately 14.4 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed AquilaChat2 34B GGUF and how large is it?

AquilaChat2 34B GGUF is developed by TheBloke, 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 AquilaChat2 34B GGUF?

AquilaChat2 34B GGUF is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

AquilaChat2 34B GGUF by TheBloke — VRAM 14.4GB

Name: AquilaChat2 34B GGUF
Author: TheBloke

AquilaChat2 34B GGUF is an open-source language model by TheBloke. Features: 34b LLM, VRAM: 14.4GB, License: other, Quantized, LLM Explorer Score: 0.1.

Aquila Base model:baai/aquilachat2-34... Base model:quantized:baai/aqui... Gguf Quantized Region:us

Model Card on HF 🤗: https://huggingface.co/TheBloke/AquilaChat2-34B-GGUF

AquilaChat2 34B GGUF Parameters and Internals

Model Type

aquila

Input Output

Input Format:

System: A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions. Human: {prompt} Assistant:

LLM Name	AquilaChat2 34B GGUF
Repository 🤗	https://huggingface.co/TheBloke/AquilaChat2-34B-GGUF
Model Name	AquilaChat2 34B
Model Creator	Beijing Academy of Artificial Intelligence
Base Model(s)	AquilaChat2 34B BAAI/AquilaChat2-34B
Model Size	34b
Required VRAM	14.4 GB
Updated	2026-06-28
Maintainer	TheBloke
Model Type	aquila
Model Files	14.4 GB 17.7 GB 16.3 GB 14.7 GB 19.1 GB 20.3 GB 19.2 GB 23.3 GB 23.9 GB 23.3 GB 27.6 GB 35.8 GB
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	AutoModel
License	other

Rank the AquilaChat2 34B 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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Note: green Score (e.g. "73.2") means that the model is better than TheBloke/AquilaChat2-34B-GGUF.