What are the hardware requirements for Swallow 7B GPTQ?

Swallow 7B GPTQ requires approximately 4.1 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Swallow 7B GPTQ and how large is it?

Swallow 7B GPTQ is developed by TheBloke, a model with 7b 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 Swallow 7B GPTQ?

Swallow 7B GPTQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Swallow 7B GPTQ by TheBloke — VRAM 4.1GB, 4K context

Name: Swallow 7B GPTQ
Author: TheBloke

Swallow 7B GPTQ is an open-source language model by TheBloke. Features: 7b LLM, VRAM: 4.1GB, Context: 4K, License: llama2, Quantized, LLM Explorer Score: 0.1.

4-bit Base model:quantized:tokyotech... Base model:tokyotech-llm/swall... En Gptq Ja Llama Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/TheBloke/Swallow-7B-GPTQ

Swallow 7B GPTQ Parameters and Internals

Model Type

text-generation

Use Cases

Areas:

Research, Text generation

Limitations:

The model has not been fully aligned with human intent and safety considerations.

Considerations:

Early stage of research. Outputs should be reviewed for alignment with safety standards.

Supported Languages

English (Fluent), Japanese (Fluent)

Training Details

Data Sources:

Japanese Wikipedia, RefinedWeb, Swallow Corpus, The Pile

Model Architecture:

Llama 2 architecture, adjusted for Japanese language data

Input Output

Accepted Modalities:

text

Output Format:

text

LLM Name	Swallow 7B GPTQ
Repository 🤗	https://huggingface.co/TheBloke/Swallow-7B-GPTQ
Model Name	Swallow 7B
Model Creator	tokyotech-llm
Base Model(s)	Swallow 7B Hf tokyotech-llm/Swallow-7b-hf
Model Size	7b
Required VRAM	4.1 GB
Updated	2026-08-01
Maintainer	TheBloke
Model Type	llama
Model Files	4.1 GB
Supported Languages	en ja
GPTQ Quantization	Yes
Quantization Type	gptq
Model Architecture	LLaMAForCausalLM
License	llama2
Context Length	4096
Model Max Length	4096
Transformers Version	4.35.2
Tokenizer Class	LlamaTokenizer
Beginning of Sentence Token	<s>
End of Sentence Token	</s>
Unk Token	<unk>
Vocabulary Size	43176
Torch Data Type	bfloat16

Rank the Swallow 7B 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

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