What are the hardware requirements for Ring Mini Sparse 2.0 Exp?

Ring Mini Sparse 2.0 Exp requires approximately 32.4 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 Ring Mini Sparse 2.0 Exp and how large is it?

Ring Mini Sparse 2.0 Exp is developed by inclusionAI, a model with 16.3b 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 Sparse 2.0 Exp?

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

Ring Mini Sparse 2.0 Exp by inclusionAI — VRAM 32.4GB, 32K context

Name: Ring Mini Sparse 2.0 Exp
Author: inclusionAI

Ring Mini Sparse 2.0 Exp is an open-source language model by inclusionAI. Features: 16.3b LLM, VRAM: 32.4GB, Context: 32K, License: mit, LLM Explorer Score: 0.21.

Bailing moe 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-sparse-2.0-exp

Ring Mini Sparse 2.0 Exp Parameters and Internals

LLM Name	Ring Mini Sparse 2.0 Exp
Repository 🤗	https://huggingface.co/inclusionAI/Ring-mini-sparse-2.0-exp
Base Model(s)	inclusionAI/Ling-mini-base-2.0-20T inclusionAI/Ling-mini-base-2.0-20T
Model Size	16.3b
Required VRAM	32.4 GB
Updated	2026-08-08
Maintainer	inclusionAI
Model Type	bailing_moe
Model Files	8.9 GB: 1-of-4 9.8 GB: 2-of-4 9.8 GB: 3-of-4 3.9 GB: 4-of-4
Supported Languages	en
Model Architecture	BailingMoeV2ForCausalLM
License	mit
Context Length	32768
Model Max Length	32768
Transformers Version	4.52.3
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|endoftext\|>
Vocabulary Size	157184
Torch Data Type	bfloat16

Rank the Ring Mini Sparse 2.0 Exp 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 Ring Mini Sparse 2.0 Exp

Best Alternatives	Context / RAM	Downloads	Likes
Ling Mini 2.0	32K / 32.4 GB	20918	198
Ring Mini 2.0	32K / 32.5 GB	460	184

Note: green Score (e.g. "73.2") means that the model is better than inclusionAI/Ring-mini-sparse-2.0-exp.