What are the hardware requirements for YuLan Mini Instruct?

YuLan Mini Instruct requires approximately 4.8 GB of VRAM and supports a context window of 28K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed YuLan Mini Instruct and how large is it?

YuLan Mini Instruct is developed by yulan-team, 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 YuLan Mini Instruct?

YuLan Mini Instruct is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

YuLan Mini Instruct by yulan-team — VRAM 4.8GB, 28K context

Name: YuLan Mini Instruct
Author: yulan-team

YuLan Mini Instruct is an open-source language model by yulan-team. Features: 2.4b LLM, VRAM: 4.8GB, Context: 28K, License: mit, Instruction-Based, LLM Explorer Score: 0.17.

Arxiv:2412.17743 Code Conversational En Endpoints compatible Instruct Llama Math Model-index Pytorch Region:us Safetensors Zh

Model Card on HF 🤗: https://huggingface.co/yulan-team/YuLan-Mini-Instruct

YuLan Mini Instruct Parameters and Internals

LLM Name	YuLan Mini Instruct
Repository 🤗	https://huggingface.co/yulan-team/YuLan-Mini-Instruct
Model Size	2.4b
Required VRAM	4.8 GB
Updated	2026-08-02
Maintainer	yulan-team
Model Type	llama
Instruction-Based	Yes
Model Files	4.8 GB 4.8 GB
Supported Languages	en zh
Model Architecture	LlamaForCausalLM
License	mit
Context Length	28723
Model Max Length	28723
Transformers Version	4.47.0
Tokenizer Class	LlamaTokenizer
Padding Token	<pad>
Vocabulary Size	99000
Torch Data Type	bfloat16

Rank the YuLan Mini Instruct 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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