What are the hardware requirements for Veyra 30M Instruct?

Veyra 30M Instruct requires approximately 0.1 GB of VRAM and supports a context window of 1K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Veyra 30M Instruct and how large is it?

Veyra 30M Instruct is developed by veyra-ai, a model with 30m 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 Veyra 30M Instruct?

Veyra 30M Instruct is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Veyra 30M Instruct by veyra-ai — VRAM 0.1GB, 1K context

Name: Veyra 30M Instruct
Author: veyra-ai

Veyra 30M Instruct is an open-source language model by veyra-ai. Features: 30m LLM, VRAM: 0.1GB, Context: 1K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.25.

Base model:finetune:veyra-ai/v... Base model:veyra-ai/veyra-30m-... Chatml Conversational En Endpoints compatible Experimental Instruct Llama Local-ai Region:us Safetensors Tiny-language-model Veyra

Model Card on HF 🤗: https://huggingface.co/veyra-ai/Veyra-30M-Instruct

Veyra 30M Instruct Parameters and Internals

LLM Name	Veyra 30M Instruct
Repository 🤗	https://huggingface.co/veyra-ai/Veyra-30M-Instruct
Base Model(s)	Veyra 30M Base veyra-ai/Veyra-30M-Base
Model Size	30m
Required VRAM	0.1 GB
Updated	2026-07-30
Maintainer	veyra-ai
Model Type	llama
Instruction-Based	Yes
Model Files	0.1 GB
Supported Languages	en
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	1024
Model Max Length	1024
Transformers Version	5.10.2
Tokenizer Class	TokenizersBackend
Padding Token	<\|pad\|>
Vocabulary Size	8192

Rank the Veyra 30M Instruct 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

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