What are the hardware requirements for Ring Mini Linear 2.0?

Ring Mini Linear 2.0 requires approximately 32.8 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Ring Mini Linear 2.0 and how large is it?

Ring Mini Linear 2.0 is developed by inclusionAI, a model with 16.4b 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 Ring Mini Linear 2.0?

Ring Mini Linear 2.0 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Ring Mini Linear 2.0 by inclusionAI — VRAM 32.8GB, 128K context

Name: Ring Mini Linear 2.0
Author: inclusionAI

Ring Mini Linear 2.0 is an open-source language model by inclusionAI. Features: 16.4b LLM, VRAM: 32.8GB, Context: 128K, License: mit, MoE, LLM Explorer Score: 0.22.

Arxiv:2510.19338 Bailing moe linear Base model:finetune:inclusiona... Base model:inclusionai/ling-mi... Conversational Custom code En Moe Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/inclusionAI/Ring-mini-linear-2.0

Ring Mini Linear 2.0 Parameters and Internals

LLM Name	Ring Mini Linear 2.0
Repository 🤗	https://huggingface.co/inclusionAI/Ring-mini-linear-2.0
Base Model(s)	inclusionAI/Ling-mini-base-2.0-20T inclusionAI/Ling-mini-base-2.0-20T
Model Size	16.4b
Required VRAM	32.8 GB
Updated	2026-07-26
Maintainer	inclusionAI
Model Type	bailing_moe_linear
Model Files	9.1 GB: 1-of-4 9.9 GB: 2-of-4 9.9 GB: 3-of-4 3.9 GB: 4-of-4
Supported Languages	en
Model Architecture	BailingMoeLinearV2ForCausalLM
License	mit
Context Length	131072
Model Max Length	131072
Transformers Version	4.56.1
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|endoftext\|>
Vocabulary Size	157184
Torch Data Type	bfloat16

Rank the Ring Mini Linear 2.0 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

Quantized Models of the Ring Mini Linear 2.0

Model	Likes	Downloads	VRAM
Ring Mini Linear 2.0 4bit	3	49	9 GB
Ring Mini Linear 2.0 GPTQ Int4	10	20	9 GB
...ing Flash Linear 2.0 GPTQ Int4	8	19	56 GB

Best Alternatives to Ring Mini Linear 2.0

Best Alternatives	Context / RAM	Downloads	Likes
Ring Mini Linear 2.0 4bit	128K / 9.2 GB	49	3