Serverless Inference API
Provides ready-to-use large model inference APIs for text, image, audio, and multimodal models, suitable for directly integrating model capabilities into business systems or prototype validation.
模力方舟(Gitee AI) is an all-in-one AI model and compute platform for inference, training, deployment, and app delivery.
模力方舟(Gitee AI) is a one-stop platform for AI model experience, inference, training, deployment, and applications. The homepage positions it as “building the best AI community in China,” and provides a unified entry point for model services, compute resources, and application distribution.
Based on publicly available pages, it covers modules such as Serverless API, model fine-tuning, the GPU compute marketplace, and the AI application marketplace. The platform also emphasizes compatibility with domestic compute, supports the full NVIDIA GPU lineup, and was among the first to integrate domestic heterogeneous compute resources such as Muxi and Ascend, making it suitable for teams that want to handle model calls, training, and deployment on one platform.
Provides ready-to-use large model inference APIs for text, image, audio, and multimodal models, suitable for directly integrating model capabilities into business systems or prototype validation.
Supports pay-as-you-go billing based on actual usage and can automatically scale resources according to load, reducing the operational cost of self-built inference infrastructure.
Provides a model fine-tuning workflow, including data import, data preprocessing, training parameter configuration, compute selection, and training result tracking, making it easier to customize models with your own data.
Offers GPU compute rental from a single card to large-scale clusters, supporting hourly rental and start/stop at any time for both training and inference tasks.
Provides application listing, service deployment, and monetization support for AI application developers, along with an elastic inference foundation.
Supports the OpenAI SDK and can integrate seamlessly with tools such as ComfyUI, Dify, n8n, and Claude Code, lowering the integration barrier.
When a team needs to quickly integrate large model capabilities into a product, it can directly use the Serverless API to call text, image, audio, or multimodal models without building its own inference service.
When you have an enterprise knowledge base, product documentation, or other private data, you can use the model fine-tuning service for customized training to create a model that better fits your business tone and task goals.
When training or inference tasks require GPU resources, you can rent compute on demand through the compute marketplace, choose the right specification from single-card to cluster configurations, and pay by usage time.
When you want to publish an AI application and reduce infrastructure operations, you can use the deployment and listing process in the application marketplace and connect to the platform's inference foundation for elastic scaling.
When your existing workflow already depends on the OpenAI SDK, ComfyUI, Dify, n8n, or Claude Code, you can use the platform's compatibility to connect models into your existing toolchain.
模力方舟(Gitee AI) provides one-stop services for model experience, inference, training, deployment, and applications. The site content shows that it covers capabilities such as Serverless API, model fine-tuning, GPU compute rental, and an AI application marketplace, making it suitable for teams that need to manage AI infrastructure and model services in a unified way.
The page shows out-of-the-box large model inference APIs, model fine-tuning services, on-demand GPU compute rental, and an AI application marketplace. For inference and application integration, the official site explicitly mentions compatibility with the OpenAI SDK and integration with mainstream tools such as ComfyUI, Dify, n8n, and Claude Code.
In the official description, Serverless API emphasizes pay-as-you-go pricing based on actual usage, while the compute marketplace emphasizes on-demand billing, hourly rental, and the ability to start and stop anytime. The pricing page currently only shows “Page not found, return to home,” and does not provide visible public pricing details.
The model fine-tuning service supports adjusting base models with your own personalized data. The page mentions that you can choose fine-tuning strategies and hyperparameters, and provides workflows for data import, data preprocessing, and training tracking. There are also two entry points, “private deployment” and “online use,” but some features are marked as coming soon.
The page clearly emphasizes compatibility with domestic compute. It mentions support for multiple domestic GPUs and heterogeneous compute resources, and includes AI skills certification content for domestic chips. If you are looking for a purely international cloud platform or a product that uses only a single overseas model provider, this platform may not be an exact match.
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