What is the Large Model Lab Lab4AI
The Large Model Lab Lab4AI is an AI practice content ecosystem community driven by high-performance computing power, with ample elastic H cards, dedicated to providing high-performance computing support and a development platform for university researchers, AI developers, and learners. By building an open and collaborative content ecosystem, it deeply integrates the three major modules of "computing resources + experiment platform + community interaction," focusing on high-computing-intensive application scenarios to support large model training, fine-tuning, and inference, and systematically promotes the efficiency of transforming large model technology from scientific research innovation to practical application.
The platform currently has various promotional activities. New users can receive 50 yuan of computing power for free, and there are more discounts for the first recharge.
Main features of the Large Model Lab Lab4AI
- High-performance and highly elastic H card GPU resources：
- A single card has 80GB of video memory, far faster than 4090 and A100
- Off-peak usage is as low as 50-55% off, more cost-effective than 4090
- Supports FP8 precision training and multi-card training, and supports NVLink + IB high-speed data transmission
- Elastic hands-on platform: On-demand invocation, flexible and controllable
- Users can independently create computing instances and freely choose GPU type and quantity.
- Supports Jupyter and VS Code editors and LLaMA Factory WebUI
- Based on cloud high-performance computing power, supports large model training, fine-tuning, and inference.
- One-click paper/project reproduction: Say goodbye to environment configuration and focus on the essence of research
- The platform provides one-click project reproduction for scenarios such as biomedicine, autonomous driving, AIGC, natural language processing, and multimodality.
- Provides one-click paper reproduction for top-journal and top-conference papers in AI research directions such as computer vision, object detection, and VLA.
- Pre-installed mainstream deep learning frameworks (such as PyTorch and TensorFlow) and commonly used dependency libraries.
- Each paper/project reproduction case comes with complete code, datasets, and pre-trained models, ready to use out of the box.
- Supports one-click startup of GPU instances, significantly reducing engineering costs.
- Premium AI course system: Learn while practicing, apply what you learn
- Covers popular directions such as large model principles, fine-tuning techniques, and application development.
- All hands-on courses are equipped with real operable Jupyter environments/VS Code environments, seamlessly connecting theory and practice.
- No local configuration required; log in and start practicing hands-on, truly mastering core technologies.
How to use the Large Model Lab Lab4AI
- Visit the platform: Visit the Large Model Lab Lab4AI official website www.lab4ai.cn , register and log in.
- Click "Reproduce Now", environment, code, datasets, and computing power are all available, and you can experience the reproduction of popular papers and projects with one click
- Click "New Instance", choose Jupyter, VS Code, and LLaMA Factory WebUI, start the instance, and run training, fine-tuning, and inference tasks. SSH remote use is also supported.
Lab4AI project reproduction experience cases:
- Case 1: Multimodal large model fine-tuning
- Qwen3-VL fine-tuning practice based on LLaMA-Factory:
- https://www.lab4ai.cn/project/detail?id=4bbc58c8c1b744b884480f1ab6b30ce6&type=project
-
- Fine-tuning Qwen3-VL with LLaMA-Factory for facial emotion recognition：
- https://www.lab4ai.cn/project/detail?id=11645e7d11fb4ac38ab7a40210762822&type=project
- Case 2: Lightweight model deployment
- Private deployment of DeepSeek-OCR in 3 minutes：
- https://www.lab4ai.cn/project/detail?id=bfe98e8c3a204f2d948e267adf4c9499&type=project
Core advantages of the Large Model Lab Lab4AI
-
One-click reproduction, saving time and effort: Integrates code, data, models, computing power, and environment into one, thoroughly solving the traditional pain points of "difficult configuration, messy dependencies, and frequent errors," greatly improving research efficiency.
- Cloud computing power, pay-as-you-go: Provides cost-effective GPU computing resources, with a flexible super-saving mode and more favorable rates during off-peak hours, enabling individual developers and students to conduct experiments at low cost.
- Ecosystem collaboration: Adapting to all-scenario needs: Supports researchers in reproducing top conference papers, learners in low-cost practice, and enterprises in validating model value.
- Research closed loop: Connects the entire chain from theory to implementation, covering the full process of "paper retrieval - AI interpretation - experiment reproduction - innovation - incubation," updates cutting-edge papers daily, and connects resources to help transform research achievements into industry solutions.
- Integration of learning and practice: Seamless connection between theory and hands-on practice. Premium courses come with Jupyter/VS Code hands-on environments, enabling "practice immediately after learning." Custom courses are set up jointly with official resources to solve the problem of "understanding theory but not knowing how to do hands-on work."
Who Lab4AI, the Large Model Laboratory, is for
- Researchers: Efficiently reproduce top conference papers, quickly follow the forefront, and conduct innovative research.
- AI learners: Obtain GPU computing power at low cost, a one-stop learning platform from beginner to expert.
- Developers: Quickly validate AI ideas and efficiently transform ideas into prototypes.
- Enterprise users: Quickly reproduce and deploy cutting-edge models in fields such as healthcare, autonomous driving, and finance.
Frequently asked questions about Lab4AI, the Large Model Laboratory
Q1: How does Lab4AI charge? What are the prices?
A: Lab4AI mainly charges based on the actual GPU resources used and usage duration. Its billing method is flexible and supports pay-as-you-go. The platform also launches promotional activities from time to time, for example, new users receive vouchers upon registration (such as 30 yuan), and joining the user group gives 20 yuan. Most importantly, V1.7 introduced the "flexible super-saving mode," where using GPU instances during off-peak hours can enjoy discounts as low as 25% of the price, greatly optimizing costs.
Q2: Does Lab4AI support development using your own local IDE?
A: Yes. The V1.7 version released in November 2025 added SSH remote connection functionality. Users can directly connect remotely to Lab4AI instance spaces through local terminals (such as VS Code Remote and PyCharm Remote Interpreter) for real-time debugging, file synchronization, and command-line operations, making the development experience closer to a local environment.
Q3: What should I do if I encounter problems when reproducing a project on Lab4AI?
A：Click Community Gifts, scan the QR code to join the dedicated user support community for Q&A.
Q4: Can the project results reproduced on Lab4AI (such as fine-tuned models) be exported?
A：Yes, they can. Lab4AI supports file upload, download, and management. After users complete model training or fine-tuning, they can download the generated model files, weights, and other results to their local machine, or use them for further deployment and applications. For specific export methods, refer to the specific instructions for each project.
