What are the hardware requirements for Veda Labs 0.5B Instruct Base?

Veda Labs 0.5B Instruct Base 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 Veda Labs 0.5B Instruct Base and how large is it?

Veda Labs 0.5B Instruct Base is developed by Hanuman2, 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 Veda Labs 0.5B Instruct Base?

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

Veda Labs 0.5B Instruct Base by Hanuman2 — VRAM 1GB, 32K context

Name: Veda Labs 0.5B Instruct Base
Author: Hanuman2

Veda Labs 0.5B Instruct Base is an open-source language model by Hanuman2. Features: 0.5b LLM, VRAM: 1GB, Context: 32K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.25.

Conversational En Instruct Qwen2 Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/Hanuman2/Veda-labs-0.5b-instruct-base

Veda Labs 0.5B Instruct Base Parameters and Internals

LLM Name	Veda Labs 0.5B Instruct Base
Repository 🤗	https://huggingface.co/Hanuman2/Veda-labs-0.5b-instruct-base
Model Size	0.5b
Required VRAM	1 GB
Updated	2026-07-26
Maintainer	Hanuman2
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	4.43.1
Tokenizer Class	SupraLabsTokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	151936
Torch Data Type	bfloat16
Errors	replace

Rank the Veda Labs 0.5B Instruct Base 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 Veda Labs 0.5B Instruct Base

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2 0.5B Abyme Merge3	128K / 1.3 GB	6	1
Qwen2 0.5B Abyme Merge2	128K / 0.3 GB	10	0
Qwen2.5 0.5B Instruct	64K / 1 GB	16	0
Qwen2.5 0.5B Instruct	32K / 1 GB	6324790	572
Sakthai Context 0.5B Tools	32K / 1 GB	474	0
Qwen R1 0.5B	32K / 1 GB	202	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
BoyBarley Sparky V3	32K / 1 GB	20	0

Note: green Score (e.g. "73.2") means that the model is better than Hanuman2/Veda-labs-0.5b-instruct-base.