What are the hardware requirements for Hippogriff 30B Chat GGUF?

Hippogriff 30B Chat GGUF requires approximately 13.5 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Hippogriff 30B Chat GGUF and how large is it?

Hippogriff 30B Chat GGUF is developed by TheBloke, a model with 30b 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 Hippogriff 30B Chat GGUF?

Hippogriff 30B Chat GGUF is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Hippogriff 30B Chat GGUF by TheBloke — VRAM 13.5GB

Name: Hippogriff 30B Chat GGUF
Author: TheBloke

Hippogriff 30B Chat GGUF is an open-source language model by TheBloke. Features: 30b LLM, VRAM: 13.5GB, License: other, Quantized, LLM Explorer Score: 0.09.

Base model:openaccess-ai-colle... Base model:quantized:openacces... Dataset:gsm8k Dataset:hellaswag Dataset:metaeval/scienceqa tex... Dataset:openai/summarize from ... Dataset:openassistant/oasst1 Dataset:qingyisi/alpaca-cot Dataset:riddle sense Dataset:teknium/gpt4-llm-clean... Dataset:teknium/gpteacher-gene... En Gguf Llama Quantized Region:us

Model Card on HF 🤗: https://huggingface.co/TheBloke/hippogriff-30b-chat-GGUF

Hippogriff 30B Chat GGUF Parameters and Internals

Model Type

llama, text-generation

Additional Notes

Hippogriff 30B Chat is an experiment built on Manticore with new datasets, removing instruction and chat datasets in favor of chat-only style prompts. It includes a de-duped subset of the Pygmalion dataset, removing Alpaca style prompts. The model's prose is improved over Manticore and handles in-context QA better but still struggles with math.

Training Details

Data Sources:

QingyiSi/Alpaca-CoT, teknium/GPT4-LLM-Cleaned, teknium/GPTeacher-General-Instruct, metaeval/ScienceQA_text_only, hellaswag, openai/summarize_from_feedback, riddle_sense, gsm8k, OpenAssistant/oasst1

Methodology:

Fine-tuning on a Llama 30B model with a focus on chat-style prompts.

Training Time:

1.5 epochs taking approximately 12 hours

Hardware Used:

8xA100 80GB

LLM Name	Hippogriff 30B Chat GGUF
Repository 🤗	https://huggingface.co/TheBloke/hippogriff-30b-chat-GGUF
Model Name	Hippogriff 30B Chat
Model Creator	Open Access AI Collective
Base Model(s)	Hippogriff 30B Chat openaccess-ai-collective/hippogriff-30b-chat
Model Size	30b
Required VRAM	13.5 GB
Updated	2026-07-31
Maintainer	TheBloke
Model Type	llama
Model Files	13.5 GB 17.3 GB 15.8 GB 14.1 GB 18.4 GB 19.6 GB 18.4 GB 22.4 GB 23.0 GB 22.4 GB 26.7 GB 34.6 GB
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	AutoModel
License	other

Rank the Hippogriff 30B 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

Best Alternatives to Hippogriff 30B Chat GGUF

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Yayi2 30B Llama GGUF	0K / 12.9 GB	511	10
...e Llama 30B Instruct 2048 GGUF	0K / 13.5 GB	865	4
VicUnlocked 30B LoRA GGUF	0K / 13.5 GB	547	1
LLaMA 30B GGUF	0K / 13.5 GB	395	5
SuperPlatty 30B GGUF	0K / 13.5 GB	368	0
Llama 30B Supercot GGUF	0K / 13.5 GB	269	0
Based 30B GGUF	0K / 13.5 GB	264	2
30B Epsilon GGUF	0K / 13.5 GB	249	4
Platypus 30B GGUF	0K / 13.5 GB	239	1
WizardLM 30B GGUF	0K / 13.5 GB	207	2

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/hippogriff-30b-chat-GGUF.