What are the hardware requirements for Alo 70M Base?

Alo 70M Base requires approximately 0.3 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 Alo 70M Base and how large is it?

Alo 70M Base is developed by spitfire4794, a model with 70m 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 Alo 70M Base?

Alo 70M Base is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Alo 70M Base by spitfire4794 — VRAM 0.3GB, 1K context

Name: Alo 70M Base
Rating: 3.25 (8 reviews)
Author: spitfire4794

Alo 70M Base is an open-source language model by spitfire4794. Features: 70m LLM, VRAM: 0.3GB, Context: 1K, License: apache-2.0, LLM Explorer Score: 0.28.

Bangla Bengali Bn Custom-tokenizer Dataset:hishab/titulm-bangla-c... Dataset:huggingfacefw/fineweb-... Llama Parameter-efficient Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/spitfire4794/Alo-70m-Base

Alo 70M Base Parameters and Internals

LLM Name	Alo 70M Base
Repository 🤗	https://huggingface.co/spitfire4794/Alo-70m-Base
Model Size	70m
Required VRAM	0.3 GB
Updated	2026-08-02
Maintainer	spitfire4794
Model Type	llama
Model Files	0.3 GB
Supported Languages	bn
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	1024
Model Max Length	1024
Transformers Version	5.13.0
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|endoftext\|>
Vocabulary Size	32768

Rank the Alo 70M 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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