What are the hardware requirements for Ring Lite 2507?

Ring Lite 2507 requires approximately 33.6 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 Lite 2507 and how large is it?

Ring Lite 2507 is developed by inclusionAI, a model with 16.8b 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 Lite 2507?

Ring Lite 2507 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Ring Lite 2507 by inclusionAI — VRAM 33.6GB, 32K context

Name: Ring Lite 2507
Author: inclusionAI

Ring Lite 2507 is an open-source language model by inclusionAI. Features: 16.8b LLM, VRAM: 33.6GB, Context: 32K, License: mit, LLM Explorer Score: 0.2.

Arxiv:2506.14731 Bailing moe Base model:finetune:inclusiona... Base model:inclusionai/ling-li... Custom code En Region:us Safetensors Sharded Tensorflow Zh

Model Card on HF 🤗: https://huggingface.co/inclusionAI/Ring-lite-2507

Ring Lite 2507 Parameters and Internals

LLM Name	Ring Lite 2507
Repository 🤗	https://huggingface.co/inclusionAI/Ring-lite-2507
Base Model(s)	inclusionAI/Ling-lite-base-1.5 inclusionAI/Ling-lite-base-1.5
Model Size	16.8b
Required VRAM	33.6 GB
Updated	2026-07-27
Maintainer	inclusionAI
Model Type	bailing_moe
Model Files	10.0 GB: 1-of-4 10.0 GB: 2-of-4 10.0 GB: 3-of-4 3.6 GB: 4-of-4
Supported Languages	zh en
Model Architecture	BailingMoeForCausalLM
License	mit
Context Length	32768
Model Max Length	32768
Transformers Version	4.51.1
Tokenizer Class	PreTrainedTokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	126464
Torch Data Type	bfloat16

Rank the Ring Lite 2507 capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

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 Lite 2507

Best Alternatives	Context / RAM	Downloads	Likes
Ling Lite 1.5	32K / 33.6 GB	31348	57
Ling Lite 1.5 2507	32K / 33.6 GB	51	77
Ling Lite 1.5 2506	32K / 33.6 GB	32	53
Ring Lite	32K / 24.4 GB	154	49
Ling Lite	32K / 24.8 GB	624	82
Ling Lite Base 1.5	32K / 25.2 GB	53	33
Ring Lite Distill Preview	16K / 33.6 GB	32	47
Ling Lite Base	16K / 33.6 GB	171	29
Ling Coder Lite	4K / 33.6 GB	93	53
Ling Coder Lite Base	4K / 33.6 GB	44	28

Note: green Score (e.g. "73.2") means that the model is better than inclusionAI/Ring-lite-2507.