What are the hardware requirements for Qwen 3.5 0.8B Hedgehog?

Qwen 3.5 0.8B Hedgehog requires approximately 1.5 GB of VRAM and supports a context window of 256K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen 3.5 0.8B Hedgehog and how large is it?

Qwen 3.5 0.8B Hedgehog is developed by MichaelAnthony, a model with 0.8b 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 Qwen 3.5 0.8B Hedgehog?

Qwen 3.5 0.8B Hedgehog is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen 3.5 0.8B Hedgehog by MichaelAnthony — VRAM 1.5GB, 256K context

Name: Qwen 3.5 0.8B Hedgehog
Author: MichaelAnthony

Qwen 3.5 0.8B Hedgehog is an open-source language model by MichaelAnthony. Features: 0.8b LLM, VRAM: 1.5GB, Context: 256K, LLM Explorer Score: 0.31.

Base model:finetune:qwen/qwen3... Base model:qwen/qwen3.5-0.8b Conversational Document-extraction Endpoints compatible Json Qwen3.5 Qwen3 5 text Rag Region:us Safetensors Simplerag

Model Card on HF 🤗: https://huggingface.co/MichaelAnthony/qwen-3.5-0.8b-Hedgehog

Qwen 3.5 0.8B Hedgehog Parameters and Internals

LLM Name	Qwen 3.5 0.8B Hedgehog
Repository 🤗	https://huggingface.co/MichaelAnthony/qwen-3.5-0.8b-Hedgehog
Base Model(s)	Qwen/Qwen3.5-0.8B Qwen/Qwen3.5-0.8B
Model Size	0.8b
Required VRAM	1.5 GB
Updated	2026-08-14
Maintainer	MichaelAnthony
Model Type	qwen3_5_text
Model Files	1.5 GB
Model Architecture	Qwen3_5ForCausalLM
Context Length	262144
Model Max Length	262144
Transformers Version	5.5.0
Tokenizer Class	TokenizersBackend
Padding Token	<\|endoftext\|>
Vocabulary Size	248320
Errors	replace

Rank the Qwen 3.5 0.8B Hedgehog 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

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