What are the hardware requirements for Ling 3.0 Tiny Base 30T?

Ling 3.0 Tiny Base 30T requires approximately 16.4 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 Ling 3.0 Tiny Base 30T and how large is it?

Ling 3.0 Tiny Base 30T is developed by inclusionAI, a model with 8.2b 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 Ling 3.0 Tiny Base 30T?

Ling 3.0 Tiny Base 30T is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Ling 3.0 Tiny Base 30T by inclusionAI — VRAM 16.4GB, 8K context

Name: Ling 3.0 Tiny Base 30T
Author: inclusionAI

Ling 3.0 Tiny Base 30T is an open-source language model by inclusionAI. Features: 8.2b LLM, VRAM: 16.4GB, Context: 8K, License: mit.

Arxiv:2507.17634 Bailing hybrid Custom code Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/inclusionAI/Ling-3.0-tiny-base-30T

Ling 3.0 Tiny Base 30T Parameters and Internals

LLM Name	Ling 3.0 Tiny Base 30T
Repository 🤗	https://huggingface.co/inclusionAI/Ling-3.0-tiny-base-30T
Model Size	8.2b
Required VRAM	16.4 GB
Updated	2026-08-23
Maintainer	inclusionAI
Model Type	bailing_hybrid
Model Files	10.6 GB: 1-of-2 5.8 GB: 2-of-2
Model Architecture	BailingMoeV3ForCausalLM
License	mit
Context Length	8192
Model Max Length	8192
Transformers Version	4.56.2
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|endoftext\|>
Vocabulary Size	157184
Torch Data Type	bfloat16

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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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