# Vintern-1B: An Efficient Multimodal Large Language Model for Vietnamese

arXiv: https://arxiv.org/abs/2408.12480 · HTML: https://mlsanity.com/paper/2408.12480/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- Placed in MLLM training and visual instruction tuning, one of 16 directions in Multimodal LLMs / vision-language models.
- Builds on 15 of its 20 references that are in the map.
- First posted on arXiv 22 Aug 2024.

## Placed in

- Multimodal LLMs / vision-language models / [MLLM training and visual instruction tuning](https://mlsanity.com/mllm/mllm-training-and-visual-instruction-tuning/)

## Builds on (most cited first, 15 of 15)

- [GPT-4 Technical Report](https://mlsanity.com/paper/2303.08774/) (2023)
- [LoRA: Low-Rank Adaptation of Large Language Models](https://mlsanity.com/paper/2106.09685/) (2021)
- [Visual Instruction Tuning](https://mlsanity.com/paper/2304.08485/) (2023)
- [Improved Baselines with Visual Instruction Tuning](https://mlsanity.com/paper/2310.03744/) (2023)
- [Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context](https://mlsanity.com/paper/2403.05530/) (2024)
- [InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks](https://mlsanity.com/paper/2312.14238/) (2023)
- [Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond](https://mlsanity.com/paper/2308.12966/) (2023)
- [Qwen2 Technical Report](https://mlsanity.com/paper/2407.10671/) (2024)
- [MiniCPM-V: A GPT-4V Level MLLM on Your Phone](https://mlsanity.com/paper/2408.01800/) (2024)
- [LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models](https://mlsanity.com/paper/2407.07895/) (2024)
- [MoE-LLaVA: Mixture of Experts for Large Vision-Language Models](https://mlsanity.com/paper/2401.15947/) (2024)
- [OpenViVQA: Task, Dataset, and Multimodal Fusion Models for Visual Question Answering in Vietnamese](https://mlsanity.com/paper/2305.04183/) (2023)
- [ViTextVQA: A Large-Scale Visual Question Answering Dataset and a Novel Multimodal Feature Fusion Method for Vietnamese Text Comprehension in Images](https://mlsanity.com/paper/2404.10652/) (2024)
- [LaVy: Vietnamese Multimodal Large Language Model](https://mlsanity.com/paper/2404.07922/) (2024)
- [UIT-HWDB: Using Transferring Method to Construct A Novel Benchmark for Evaluating Unconstrained Handwriting Image Recognition in Vietnamese](https://mlsanity.com/paper/2211.05407/) (2022)

## Built on by (most cited first, 12 of 12)

- [Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling](https://mlsanity.com/paper/2412.05271/) (2024)
- [Pangea: A Fully Open Multilingual Multimodal LLM for 39 Languages](https://mlsanity.com/paper/2410.16153/) (2024)
- [V2PE: Improving Multimodal Long-Context Capability of Vision-Language Models with Variable Visual Position Encoding](https://mlsanity.com/paper/2412.09616/) (2024)
- [Large Multimodal Models for Low-Resource Languages: A Survey](https://mlsanity.com/paper/2502.05568/) (2025)
- [AutoJudger: An Agent-Driven Framework for Efficient Benchmarking of MLLMs](https://mlsanity.com/paper/2505.21389/) (2025)
- [CONSTANT: Towards High-Quality One-Shot Handwriting Generation with Patch Contrastive Enhancement and Style-Aware Quantization](https://mlsanity.com/paper/2603.07543/) (2026)
- [A Survey on Vietnamese Document Analysis and Recognition: Challenges and Future Directions](https://mlsanity.com/paper/2506.05061/) (2025)
- [Fusionista2.0: Efficiency Retrieval System for Large-Scale Datasets](https://mlsanity.com/paper/2511.12255/) (2025)
- [AutoViVQA: A Large-Scale Automatically Constructed Dataset for Vietnamese Visual Question Answering](https://mlsanity.com/paper/2603.09689/) (2026)
- [ViX-Ray: A Vietnamese Chest X-Ray Dataset for Vision-Language Models](https://mlsanity.com/paper/2603.15513/) (2026)
- [U-CESE: Unified Clip-based Event Search Engine for AI Challenge HCMC 2025](https://mlsanity.com/paper/2605.23274/) (2026)
- [VietAIDetector: An Open-Source Zero-Shot Detector for Vietnamese AI-Generated Text](https://mlsanity.com/paper/2608.25478/) (2026)

## Abstract (arXiv)

In this report, we introduce Vintern-1B, a reliable 1-billion-parameters multimodal large language model (MLLM) for Vietnamese language tasks. By integrating the Qwen2-0.5B-Instruct language model with the InternViT-300M-448px visual model, Vintern-1B is optimized for a range of applications, including optical character recognition (OCR), document extraction, and general question-answering in Vietnamese context. The model is fine-tuned on an extensive dataset of over 3 million image-question-answer pairs, achieving robust performance and reliable results across multiple Vietnamese language benchmarks like OpenViVQA and ViTextVQA. Vintern-1B is small enough to fit into various on-device applications easily. Additionally, we have open-sourced several Vietnamese vision question answering (VQA) datasets for text and diagrams, created with Gemini 1.5 Flash. Our models are available at: https://huggingface.co/5CD-AI/Vintern-1B-v2.