What are the hardware requirements for Tulu 30B SuperHOT 8K GPTQ?

Tulu 30B SuperHOT 8K GPTQ requires approximately 16.9 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Tulu 30B SuperHOT 8K GPTQ and how large is it?

Tulu 30B SuperHOT 8K GPTQ 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 Tulu 30B SuperHOT 8K GPTQ?

Tulu 30B SuperHOT 8K GPTQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Tulu 30B SuperHOT 8K GPTQ by TheBloke — VRAM 16.9GB, 8K context

Name: Tulu 30B SuperHOT 8K GPTQ
Author: TheBloke

Tulu 30B SuperHOT 8K GPTQ is an open-source language model by TheBloke. Features: 30b LLM, VRAM: 16.9GB, Context: 8K, License: other, Quantized, LLM Explorer Score: 0.07.

4-bit Custom code Ext 8k Gptq Llama Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/TheBloke/Tulu-30B-SuperHOT-8K-GPTQ

Tulu 30B SuperHOT 8K GPTQ Parameters and Internals

Model Type

GPTQ 4bit

Additional Notes

An experimental GPTQ offering up to 8K context size; requires specific loaders and settings for optimal use.

Input Output

Performance Tips:

Using the full 8K context on a 30B model will exceed 24GB VRAM.

LLM Name	Tulu 30B SuperHOT 8K GPTQ
Repository 🤗	https://huggingface.co/TheBloke/Tulu-30B-SuperHOT-8K-GPTQ
Model Size	30b
Required VRAM	16.9 GB
Updated	2026-08-01
Maintainer	TheBloke
Model Type	llama
Model Files	16.9 GB
GPTQ Quantization	Yes
Context Length	8k
Quantization Type	gptq
Model Architecture	LlamaForCausalLM
License	other
Context Length	8192
Model Max Length	8192
Transformers Version	4.30.0.dev0
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32001
Torch Data Type	float16

Rank the Tulu 30B SuperHOT 8K GPTQ 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 Tulu 30B SuperHOT 8K GPTQ

Best Alternatives	Context / RAM	Downloads	Likes
... 30B Supercot SuperHOT 8K GPTQ	8K / 16.9 GB	69	5
GPlatty 30B SuperHOT 8K GPTQ	8K / 16.9 GB	10	7
Platypus 30B SuperHOT 8K GPTQ	8K / 16.9 GB	5	4
Yayi2 30B Llama GPTQ	4K / 17 GB	12	2
WizardLM 30B GPTQ	2K / 16.9 GB	645	18
...2 Llama 30B 7K Steps Gptq 2bit	2K / 9.5 GB	9	2
Llama 30B FINAL MODEL MINI	2K / 19.4 GB	5	1
WizardLM 30B V1.0 GPTQ	2K / 16.9 GB	4	1
...2 Llama 30B 7K Steps Gptq 4bit	2K / 17.5 GB	5	3
...Assistant SFT 7 Llama 30B GPTQ	2K / 16.9 GB	124	35

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Tulu-30B-SuperHOT-8K-GPTQ.