What are the hardware requirements for Vertex 0.6 15M Base?

Vertex 0.6 15M Base requires approximately 0.1 GB of VRAM and supports a context window of 2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Vertex 0.6 15M Base and how large is it?

Vertex 0.6 15M Base is developed by VertexResearch, a model with 15m 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 Vertex 0.6 15M Base?

Vertex 0.6 15M Base is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Vertex 0.6 15M Base by VertexResearch — VRAM 0.1GB, 2K context

Name: Vertex 0.6 15M Base
Author: VertexResearch

Vertex 0.6 15M Base is an open-source language model by VertexResearch. Features: 15m LLM, VRAM: 0.1GB, Context: 2K, License: apache-2.0, LLM Explorer Score: 0.31.

Dataset:openbmb/ultra-fineweb Dataset:openbmb/ultra-fineweb-... En Qwen3 Region:us Safetensors Tiny Vertex

Model Card on HF 🤗: https://huggingface.co/VertexResearch/Vertex-0.6-15M-Base

Vertex 0.6 15M Base Parameters and Internals

LLM Name	Vertex 0.6 15M Base
Repository 🤗	https://huggingface.co/VertexResearch/Vertex-0.6-15M-Base
Model Size	15m
Required VRAM	0.1 GB
Updated	2026-09-07
Maintainer	VertexResearch
Model Type	qwen3
Model Files	0.1 GB
Supported Languages	en
Model Architecture	Qwen3ForCausalLM
License	apache-2.0
Context Length	2048
Model Max Length	2048
Transformers Version	5.15.1
Tokenizer Class	TokenizersBackend
Padding Token	<\|pad\|>
Vocabulary Size	20000

Rank the Vertex 0.6 15M Base 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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