What are the hardware requirements for Queen V2?

Queen V2 requires approximately 0.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Queen V2 and how large is it?

Queen V2 is developed by Crawlnet, a model with 75.5m 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 Queen V2?

Queen V2 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Queen V2 by Crawlnet — VRAM 0.2GB

Name: Queen V2
Author: Crawlnet

Queen V2 is an open-source language model by Crawlnet. Features: 75.5m LLM, VRAM: 0.2GB, License: apache-2.0, LLM Explorer Score: 0.33.

Crawlnet Crypto En From-scratch Nanochat Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/Crawlnet/queen-v2

Queen V2 Parameters and Internals

LLM Name	Queen V2
Repository 🤗	https://huggingface.co/Crawlnet/queen-v2
Model Size	75.5m
Required VRAM	0.2 GB
Updated	2026-10-09
Maintainer	Crawlnet
Model Files	0.2 GB
Supported Languages	en
License	apache-2.0

Rank the Queen V2 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