What are the hardware requirements for Reasoning 0.5B?

Reasoning 0.5B 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 Reasoning 0.5B and how large is it?

Reasoning 0.5B is developed by KingNish, 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 Reasoning 0.5B?

Reasoning 0.5B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Reasoning 0.5B by KingNish — VRAM 1GB, 32K context

Name: Reasoning 0.5B
Author: KingNish

Reasoning 0.5B is an open-source language model by KingNish. Features: 0.5b LLM, VRAM: 1GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.17.

Ara Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-0.5b-i... Conversational Dataset:kingnish/reasoning-bas... Deu Endpoints compatible Eng Fra Instruct Ita Jpn Kor Por Pytorch Qwen2 Reasoning Region:us Rus Safetensors Sft Spa Tha Trl Unsloth Vie Zho

Model Card on HF 🤗: https://huggingface.co/KingNish/Reasoning-0.5b

Reasoning 0.5B Parameters and Internals

Model Type

text generation

Additional Notes

The model is a first iteration and was trained for testing purposes. It uses a reasoning-based approach without special tokens. It was trained with Unsoth library to achieve a 2x faster training.

Supported Languages

en (full)

Training Details

Data Sources:

KingNish/reasoning-base-20k

Data Volume:

10k rows

LLM Name	Reasoning 0.5B
Repository 🤗	https://huggingface.co/KingNish/Reasoning-0.5b
Base Model(s)	Qwen/Qwen2.5-0.5B-Instruct Qwen/Qwen2.5-0.5B-Instruct
Model Size	0.5b
Required VRAM	1 GB
Updated	2026-07-28
Maintainer	KingNish
Model Type	qwen2
Instruction-Based	Yes
Model Files	1.0 GB 1.0 GB
Supported Languages	en
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.44.2
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	float16
Errors	replace

Rank the Reasoning 0.5B 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

Best Alternatives to Reasoning 0.5B

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2 0.5B Abyme Merge3	128K / 1.3 GB	13	1
Qwen2 0.5B Abyme Merge2	128K / 0.3 GB	14	0
Qwen2.5 0.5B Instruct	64K / 1 GB	16	0
Qwen2.5 0.5B Instruct	32K / 1 GB	6324790	572
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
...ext Aware Abstention Qwen 0.5B	32K / 2 GB	48	0
Q SS 0.5B Reasoning Math	32K / 1 GB	12	2

Note: green Score (e.g. "73.2") means that the model is better than KingNish/Reasoning-0.5b.