What are the hardware requirements for EXAONE ExaDialogue 2.4B?

EXAONE ExaDialogue 2.4B requires approximately 4.8 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 ExaDialogue 2.4B and how large is it?

EXAONE ExaDialogue 2.4B is developed by lunar1020, a model with 2.4b 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 ExaDialogue 2.4B?

EXAONE ExaDialogue 2.4B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

EXAONE ExaDialogue 2.4B by lunar1020 — VRAM 4.8GB, 32K context

Name: EXAONE ExaDialogue 2.4B
Author: lunar1020

EXAONE ExaDialogue 2.4B is an open-source language model by lunar1020. Features: 2.4b LLM, VRAM: 4.8GB, Context: 32K, License: other, LLM Explorer Score: 0.31.

Conversational Dataset:myungseung/kakaotalk m... Endpoints compatible Exaone Exaone-3.5 Ko Llama Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/lunar1020/EXAONE-ExaDialogue-2.4B

EXAONE ExaDialogue 2.4B Parameters and Internals

LLM Name	EXAONE ExaDialogue 2.4B
Repository 🤗	https://huggingface.co/lunar1020/EXAONE-ExaDialogue-2.4B
Model Size	2.4b
Required VRAM	4.8 GB
Updated	2026-09-10
Maintainer	lunar1020
Model Type	llama
Model Files	4.8 GB
Supported Languages	ko
Model Architecture	LlamaForCausalLM
License	other
Context Length	32768
Model Max Length	32768
Transformers Version	5.8.0
Tokenizer Class	GPT2Tokenizer
Padding Token	[PAD]
Vocabulary Size	102400
Errors	replace

Rank the EXAONE ExaDialogue 2.4B 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

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