What are the hardware requirements for Qwen3.5 0.8B Fable GPT6?

Qwen3.5 0.8B Fable GPT6 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 Qwen3.5 0.8B Fable GPT6 and how large is it?

Qwen3.5 0.8B Fable GPT6 is developed by Shreesha-2011, 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 Qwen3.5 0.8B Fable GPT6?

Qwen3.5 0.8B Fable GPT6 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3.5 0.8B Fable GPT6 by Shreesha-2011 — VRAM 1.5GB, 256K context

Name: Qwen3.5 0.8B Fable GPT6
Author: Shreesha-2011

Qwen3.5 0.8B Fable GPT6 is an open-source language model by Shreesha-2011. Features: 0.8b LLM, VRAM: 1.5GB, Context: 256K, LLM Explorer Score: 0.3.

Arxiv:1910.09700 Conversational Endpoints compatible Qwen3 5 text Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/Shreesha-2011/Qwen3.5-0.8B-Fable-GPT6

Qwen3.5 0.8B Fable GPT6 Parameters and Internals

LLM Name	Qwen3.5 0.8B Fable GPT6
Repository 🤗	https://huggingface.co/Shreesha-2011/Qwen3.5-0.8B-Fable-GPT6
Model Size	0.8b
Required VRAM	1.5 GB
Updated	2026-10-02
Maintainer	Shreesha-2011
Model Type	qwen3_5_text
Model Files	1.5 GB
Model Architecture	Qwen3_5ForCausalLM
Context Length	262144
Model Max Length	262144
Transformers Version	5.17.0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	248320
Errors	replace

Rank the Qwen3.5 0.8B Fable GPT6 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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