What are the hardware requirements for Sakthai Context 0.5B Tools?

Sakthai Context 0.5B Tools 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 Sakthai Context 0.5B Tools and how large is it?

Sakthai Context 0.5B Tools is developed by Nanthasit, 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 Sakthai Context 0.5B Tools?

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

Sakthai Context 0.5B Tools by Nanthasit — VRAM 1GB, 32K context

Name: Sakthai Context 0.5B Tools
Author: Nanthasit

Sakthai Context 0.5B Tools is an open-source language model by Nanthasit. Features: 0.5b LLM, VRAM: 1GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.28.

Agent Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-0.5b-i... Benchmark Conversational Dataset:nanthasit/sakthai-benc... Dataset:nanthasit/sakthai-comb... Edge En Endpoints compatible Eval Eval-results Function-calling House-of-sak Instruct Lightweight Low-resource Merge Model-index Ollama On-device Qwen Qwen2 Qwen2.5 Raspberry-pi Region:us Safetensors Sakthai Slm Small-language-model Tool-calling Tool-use

Model Card on HF 🤗: https://huggingface.co/Nanthasit/sakthai-context-0.5b-tools

Sakthai Context 0.5B Tools Parameters and Internals

LLM Name	Sakthai Context 0.5B Tools
Repository 🤗	https://huggingface.co/Nanthasit/sakthai-context-0.5b-tools
Base Model(s)	Qwen/Qwen2.5-0.5B-Instruct Qwen/Qwen2.5-0.5B-Instruct
Model Size	0.5b
Required VRAM	1 GB
Updated	2026-08-01
Maintainer	Nanthasit
Model Type	qwen2
Instruction-Based	Yes
Model Files	1.0 GB
Supported Languages	en
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	5.14.1
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Errors	replace

Rank the Sakthai Context 0.5B Tools 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 Sakthai Context 0.5B Tools

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2 0.5B Abyme Merge3	128K / 1.3 GB	11	1
Qwen2 0.5B Abyme Merge2	128K / 0.3 GB	13	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
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
DAC5.4 0.5B	32K / 1 GB	12	0

Note: green Score (e.g. "73.2") means that the model is better than Nanthasit/sakthai-context-0.5b-tools.