What are the hardware requirements for AV BI Qwen2.5 14B PT BR Instruct?

AV BI Qwen2.5 14B PT BR Instruct requires approximately 29.7 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed AV BI Qwen2.5 14B PT BR Instruct and how large is it?

AV BI Qwen2.5 14B PT BR Instruct is developed by amadeusai, a model with 14b 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 AV BI Qwen2.5 14B PT BR Instruct?

AV BI Qwen2.5 14B PT BR Instruct is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

AV BI Qwen2.5 14B PT BR Instruct by amadeusai — VRAM 29.7GB, 128K context

Name: AV BI Qwen2.5 14B PT BR Instruct
Author: amadeusai

AV BI Qwen2.5 14B PT BR Instruct is an open-source language model by amadeusai. Features: 14b LLM, VRAM: 29.7GB, Context: 128K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.16.

Autotrain compatible Base model:finetune:qwen/qwen2... Base model:qwen/qwen2.5-14b Chat Conversational Endpoints compatible Instruct Pt Qwen2 Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/amadeusai/AV-BI-Qwen2.5-14B-PT-BR-Instruct

AV BI Qwen2.5 14B PT BR Instruct Parameters and Internals

LLM Name	AV BI Qwen2.5 14B PT BR Instruct
Repository 🤗	https://huggingface.co/amadeusai/AV-BI-Qwen2.5-14B-PT-BR-Instruct
Base Model(s)	Qwen/Qwen2.5-14B Qwen/Qwen2.5-14B
Model Size	14b
Required VRAM	29.7 GB
Updated	2025-05-20
Maintainer	amadeusai
Model Type	qwen2
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-6 5.0 GB: 2-of-6 5.0 GB: 3-of-6 5.0 GB: 4-of-6 5.0 GB: 5-of-6 4.7 GB: 6-of-6 0.0 GB
Supported Languages	en
Model Architecture	Qwen2ForCausalLM
License	apache-2.0
Context Length	131072
Model Max Length	131072
Transformers Version	4.46.3
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Vocabulary Size	152064
Torch Data Type	bfloat16
Errors	replace

Rank the AV BI Qwen2.5 14B PT BR 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

Best Alternatives to AV BI Qwen2.5 14B PT BR Instruct

Best Alternatives	Context / RAM	Downloads	Likes
Qwen2.5 14B Instruct 1M	986K / 29.6 GB	10388	342
T3Q Qwen2.5 14B V1.0 E3	986K / 29.7 GB	852	28
ZYH LLM Qwen2.5 14B V4	986K / 29.7 GB	27	8
Qwen2.5 14B 1M YOYO V3	986K / 29.7 GB	254	4
Qwen2.5 14B YOYO V4	986K / 29.7 GB	20	5
Qwen2.5 14B YOYO Latest V2	986K / 29.7 GB	129	0
ZYH LLM Qwen2.5 14B V3	986K / 29.7 GB	23	8
...14B Instruct 1M GRPO Reasoning	986K / 29.7 GB	11	4
Impish QWEN 14B 1M	986K / 29.7 GB	56	26
Q2.5 14B Instruct 1M Harmony	986K / 29.7 GB	3	1

Note: green Score (e.g. "73.2") means that the model is better than amadeusai/AV-BI-Qwen2.5-14B-PT-BR-Instruct.