What are the hardware requirements for EXAONE 3.5 7.8B Instruct AWQ?

EXAONE 3.5 7.8B Instruct AWQ requires approximately 5.3 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed EXAONE 3.5 7.8B Instruct AWQ and how large is it?

EXAONE 3.5 7.8B Instruct AWQ is developed by LGAI-EXAONE, a model with 7.8b 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 EXAONE 3.5 7.8B Instruct AWQ?

EXAONE 3.5 7.8B Instruct AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

EXAONE 3.5 7.8B Instruct AWQ by LGAI-EXAONE — VRAM 5.3GB, 32K context

Name: EXAONE 3.5 7.8B Instruct AWQ
Author: LGAI-EXAONE

EXAONE 3.5 7.8B Instruct AWQ is an open-source language model by LGAI-EXAONE. Features: 7.8b LLM, VRAM: 5.3GB, Context: 32K, License: other, Quantized, Instruction-Based, LLM Explorer Score: 0.24.

Arxiv:2412.04862 4-bit Awq Conversational Custom code En Exaone Exaone-3.5 Instruct Ko Lg-ai Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/LGAI-EXAONE/EXAONE-3.5-7.8B-Instruct-AWQ

EXAONE 3.5 7.8B Instruct AWQ Parameters and Internals

LLM Name	EXAONE 3.5 7.8B Instruct AWQ
Repository 🤗	https://huggingface.co/LGAI-EXAONE/EXAONE-3.5-7.8B-Instruct-AWQ
Base Model(s)	EXAONE-3.5-7.8B-Instruct /EXAONE-3.5-7.8B-Instruct
Model Size	7.8b
Required VRAM	5.3 GB
Updated	2026-08-09
Maintainer	LGAI-EXAONE
Model Type	exaone
Instruction-Based	Yes
Model Files	4.5 GB: 1-of-2 0.8 GB: 2-of-2
Supported Languages	en ko
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	ExaoneForCausalLM
License	other
Context Length	32768
Model Max Length	32768
Transformers Version	4.43.0
Tokenizer Class	GPT2Tokenizer
Padding Token	[PAD]
Vocabulary Size	102400
Torch Data Type	float16
Activation Function	silu

Rank the EXAONE 3.5 7.8B Instruct AWQ capabilities

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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 EXAONE 3.5 7.8B Instruct AWQ

Best Alternatives	Context / RAM	Downloads	Likes
EXAONE 3.5 7.8B Instruct	32K / 31.2 GB	515747	159
EXAONE Deep 7.8B	32K / 15.6 GB	2351	104
... 3.5 7.8B Instruct Abliterated	32K / 31.2 GB	153	6

Note: green Score (e.g. "73.2") means that the model is better than LGAI-EXAONE/EXAONE-3.5-7.8B-Instruct-AWQ.