What are the hardware requirements for HyBird 100M?

HyBird 100M requires approximately 0.4 GB of VRAM and supports a context window of 10K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed HyBird 100M and how large is it?

HyBird 100M is developed by Yeeee1211, a model with 100m 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 HyBird 100M?

HyBird 100M is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

HyBird 100M by Yeeee1211 — VRAM 0.4GB, 10K context

Name: HyBird 100M
Author: Yeeee1211

HyBird 100M is an open-source language model by Yeeee1211. Features: 100m LLM, VRAM: 0.4GB, Context: 10K, License: mit, LLM Explorer Score: 0.29.

Chinese Cpu-inference Dataset:jingyaogong/minimind d... Kda Linear-attention Pytorch Region:us Zh

Model Card on HF 🤗: https://huggingface.co/Yeeee1211/hyBird-100M

HyBird 100M Parameters and Internals

LLM Name	HyBird 100M
Repository 🤗	https://huggingface.co/Yeeee1211/hyBird-100M
Model Size	100m
Required VRAM	0.4 GB
Updated	2026-10-06
Maintainer	Yeeee1211
Model Files	0.4 GB
Supported Languages	zh
License	mit
Context Length	10240
Model Max Length	10240
Vocabulary Size	32768

Rank the HyBird 100M 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