What are the hardware requirements for Qwen Dumb Merged?

Qwen Dumb Merged requires approximately 1 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 Qwen Dumb Merged and how large is it?

Qwen Dumb Merged is developed by shimbaaa, a model with 0.5b 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 Dumb Merged?

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

Qwen Dumb Merged by shimbaaa — VRAM 1GB, 32K context

Name: Qwen Dumb Merged
Author: shimbaaa

Qwen Dumb Merged is an open-source language model by shimbaaa. Features: 0.5b LLM, VRAM: 1GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.31.

4bit Conversational En Endpoints compatible Instruct Quantized Qwen2 Region:us Safetensors Unsloth

Model Card on HF 🤗: https://huggingface.co/shimbaaa/Qwen-Dumb-Merged

Qwen Dumb Merged Parameters and Internals

LLM Name	Qwen Dumb Merged
Repository 🤗	https://huggingface.co/shimbaaa/Qwen-Dumb-Merged
Base Model(s)	unsloth/qwen2.5-0.5b-instruct-unsloth-bnb-4bit unsloth/qwen2.5-0.5b-instruct-unsloth-bnb-4bit
Model Size	0.5b
Required VRAM	1 GB
Updated	2026-09-06
Maintainer	shimbaaa
Model Type	qwen2
Instruction-Based	Yes
Model Files	1.0 GB
Supported Languages	en
Quantization Type	4bit
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|vision_pad\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Qwen Dumb Merged 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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