What are the hardware requirements for Qwen Qwen1.5 0.5B1716489573?

Qwen Qwen1.5 0.5B1716489573 requires approximately 0.9 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 Qwen1.5 0.5B1716489573 and how large is it?

Qwen Qwen1.5 0.5B1716489573 is developed by jenniellama, a model with 464m 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 Qwen1.5 0.5B1716489573?

Qwen Qwen1.5 0.5B1716489573 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen Qwen1.5 0.5B1716489573 by jenniellama — VRAM 0.9GB, 32K context

Name: Qwen Qwen1.5 0.5B1716489573
Author: jenniellama

Qwen Qwen1.5 0.5B1716489573 is an open-source language model by jenniellama. Features: 464m LLM, VRAM: 0.9GB, Context: 32K, Merged, LLM Explorer Score: 0.12.

Merged Model Arxiv:1910.09700 Conversational Endpoints compatible Qwen2 Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/jenniellama/Qwen-Qwen1.5-0.5B1716489573

Qwen Qwen1.5 0.5B1716489573 Parameters and Internals

LLM Name	Qwen Qwen1.5 0.5B1716489573
Repository 🤗	https://huggingface.co/jenniellama/Qwen-Qwen1.5-0.5B1716489573
Merged Model	Yes
Model Size	464m
Required VRAM	0.9 GB
Updated	2026-07-27
Maintainer	jenniellama
Model Type	qwen2
Model Files	0.9 GB
Model Architecture	Qwen2ForCausalLM
Context Length	32768
Model Max Length	32768
Transformers Version	4.40.2
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	float16
Errors	replace

Rank the Qwen Qwen1.5 0.5B1716489573 capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

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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Zeta 2	32K / 1.9 GB	45	3
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...ind NuExtract Tiny 15 Examples	32K / 1.9 GB	7	0
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Note: green Score (e.g. "73.2") means that the model is better than jenniellama/Qwen-Qwen1.5-0.5B1716489573.