What are the hardware requirements for Qwen2.5 0.5B Instruct Pruned Distill Inshort?

Qwen2.5 0.5B Instruct Pruned Distill Inshort requires approximately 0.6 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 Qwen2.5 0.5B Instruct Pruned Distill Inshort and how large is it?

Qwen2.5 0.5B Instruct Pruned Distill Inshort is developed by nis12ram, 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 Qwen2.5 0.5B Instruct Pruned Distill Inshort?

Qwen2.5 0.5B Instruct Pruned Distill Inshort is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen2.5 0.5B Instruct Pruned Distill Inshort by nis12ram — VRAM 0.6GB, 32K context

Name: Qwen2.5 0.5B Instruct Pruned Distill Inshort
Author: nis12ram

Qwen2.5 0.5B Instruct Pruned Distill Inshort is an open-source language model by nis12ram. Features: 0.5b LLM, VRAM: 0.6GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.18.

Base model:finetune:nis12ram/q... Base model:nis12ram/qwen2.5-0.... Conversational Dataset:shivam9980/inshorts-en... En Endpoints compatible Instruct Qwen2 Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/nis12ram/qwen2.5-0.5B-Instruct-pruned-distill-Inshort

Qwen2.5 0.5B Instruct Pruned Distill Inshort Parameters and Internals

LLM Name	Qwen2.5 0.5B Instruct Pruned Distill Inshort
Repository 🤗	https://huggingface.co/nis12ram/qwen2.5-0.5B-Instruct-pruned-distill-Inshort
Base Model(s)	nis12ram/qwen2.5-0.5B-Instruct-pruned-Inshort nis12ram/qwen2.5-0.5B-Instruct-pruned-Inshort
Model Size	0.5b
Required VRAM	0.6 GB
Updated	2026-05-13
Maintainer	nis12ram
Model Type	qwen2
Instruction-Based	Yes
Model Files	0.6 GB
Supported Languages	en
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.52.4
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	float16
Errors	replace

Rank the Qwen2.5 0.5B Instruct Pruned Distill Inshort 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

Best Alternatives to Qwen2.5 0.5B Instruct Pruned Distill Inshort

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2 0.5B Abyme Merge3	128K / 1.3 GB	22	1
Qwen2 0.5B Abyme Merge2	128K / 0.3 GB	20	0
Qwen2.5 0.5B Instruct	64K / 1 GB	16	0
Qwen2.5 0.5B Instruct	32K / 1 GB	6324790	572
Rifa Nano 0.5B	32K / 1 GB	703	0
Pulsar AI Final	32K / 1 GB	185	2
Chichu 2.0 500M Instruct	32K / 1 GB	212	2
Sakthai Context 0.5B Tools	32K / 1 GB	474	0
Qwen R1 0.5B	32K / 1 GB	202	2
Veda Labs 0.5B Instruct Base	32K / 1 GB	30	2

Note: green Score (e.g. "73.2") means that the model is better than nis12ram/qwen2.5-0.5B-Instruct-pruned-distill-Inshort.