What are the hardware requirements for Aitana 2B S Tourism Base?

Aitana 2B S Tourism Base requires approximately 4.5 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Aitana 2B S Tourism Base and how large is it?

Aitana 2B S Tourism Base is developed by gplsi, a model with 2b 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 Aitana 2B S Tourism Base?

Aitana 2B S Tourism Base is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Aitana 2B S Tourism Base by gplsi — VRAM 4.5GB, 8K context

Name: Aitana 2B S Tourism Base
Author: gplsi

Aitana 2B S Tourism Base is an open-source language model by gplsi. Features: 2b LLM, VRAM: 4.5GB, Context: 8K, License: apache-2.0, Quantized, LLM Explorer Score: 0.21.

Alia Base model:gplsi/aitana-2b-s-t... Base model:quantized:gplsi/ait... Ca Catalan Dataset:gplsi/alia tourism En Endpoints compatible English Es Gguf Gplsi Llama Quantized Region:us Safetensors Spanish Tourism Valencian

Model Card on HF 🤗: https://huggingface.co/gplsi/Aitana-2B-S-tourism-base

Aitana 2B S Tourism Base Parameters and Internals

LLM Name	Aitana 2B S Tourism Base
Repository 🤗	https://huggingface.co/gplsi/Aitana-2B-S-tourism-base
Base Model(s)	Aitana 2B S Tourism Base gplsi/Aitana-2B-S-tourism-base
Model Size	2b
Required VRAM	4.5 GB
Updated	2026-06-28
Maintainer	gplsi
Model Type	llama
Model Files	4.5 GB 4.5 GB
Supported Languages	ca es en
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	8192
Model Max Length	8192
Transformers Version	4.56.2
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	256000

Rank the Aitana 2B S Tourism 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

Quantized Models of the Aitana 2B S Tourism Base

Model	Likes	Downloads	VRAM
Aitana 2B S Tourism Base	0	221	4 GB

Best Alternatives to Aitana 2B S Tourism Base

Best Alternatives	Context / RAM	Downloads	Likes
...inicpm5 2B Distilled Reasoning	128K / 5 GB	770	1
Aitana 2B S Base	8K / 4.5 GB	559	1
HelpingAI2.5 2B	8K / 1.1 GB	70	2
HelpingAI2.5 2B	8K / 1.1 GB	19	2
Veyra2 30M Base 2B Tokens	1K / 0.1 GB	404	1
MiniCPM5 2B 8bit	128K / 2.7 GB	734	6
MiniCPM5 2B OptiQ 4bit	128K / 1.9 GB	317	3
MiniCPM5 2B Mlx 4Bit	128K / 1.4 GB	286	1
MiniCPM5 2B MLX 8bit	128K / 2.7 GB	193	3
MiniCPM5 2B MLX 6bit	128K / 2 GB	192	1

Note: green Score (e.g. "73.2") means that the model is better than gplsi/Aitana-2B-S-tourism-base.