What are the hardware requirements for Legislinho?

Legislinho requires approximately 4.1 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 Legislinho and how large is it?

Legislinho is developed by MagusCorp, a model with 7.5b 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 Legislinho?

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

Legislinho by MagusCorp — VRAM 4.1GB, 32K context

Name: Legislinho
Author: MagusCorp

Legislinho is an open-source language model by MagusCorp. Features: 7.5b LLM, VRAM: 4.1GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.11.

4-bit Bitsandbytes Conversational Endpoints compatible Mistral Model-index Pt Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/MagusCorp/legislinho

Legislinho Parameters and Internals

LLM Name	Legislinho
Repository 🤗	https://huggingface.co/MagusCorp/legislinho
Model Size	7.5b
Required VRAM	4.1 GB
Updated	2026-08-07
Maintainer	MagusCorp
Model Type	mistral
Model Files	4.1 GB
Supported Languages	pt
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.38.0.dev0
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32002
Torch Data Type	float16

Rank the Legislinho 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

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ClimateChat	32K / 15 GB	17	2
Finchat298 Mistral7B FT 650	32K / 4.1 GB	5	0
Finchat298 Mistral7B FT3	32K / 4.1 GB	5	0
...iceday Finetune Articles V4 V3	32K / 4.7 GB	7	0
Technical Analysis Unsloth V3	32K / 4.1 GB	6	3
0dAI 7.5B V2 4bpw	32K / 3.8 GB	14	3
0dAI 7.5B V2 8bpw	32K / 7.3 GB	14	0
Mistral MoE Lora	32K / 4.1 GB	4	1
Mymodel V2	32K / 30.1 GB	6	0
Mymodel V1	32K / 59 GB	5	0

Note: green Score (e.g. "73.2") means that the model is better than MagusCorp/legislinho.