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Cube Studio
Cube Studio is a cloud-native machine learning platform that manages the full MLOps lifecycle, distributed model training, and large model inference services.
Cube Studio is an open-source, cloud-native platform designed for the complete machine learning and deep learning lifecycle. It provides tools for online notebook development, drag-and-drop pipeline orchestration, and distributed training across multiple machines and cards. The platform supports large language model operations, including supervised fine-tuning, reward modeling, and reinforcement learning for models like DeepSeek. Users can use VGPU virtualization for inference services and utilize an integrated AI model marketplace and private knowledge base. The system supports various frameworks including PyTorch, TensorFlow, MXNet, DeepSpeed, and Ray, along with domestic hardware ecosystems like Ascend NPU. Please note that the project repository is currently archived.
Cube Studio at a glance
Key features
- Drag-and-drop pipeline orchestration
- Multi-machine and multi-card distributed training
- VGPU virtualization for inference services
- Automated data labeling
- Support for PyTorch, TensorFlow, and DeepSpeed frameworks
- Large language model fine-tuning and reinforcement learning
- Integration with vLLM, Ollama, and Mindie for inference
Use it for
- Managing end-to-end MLOps lifecycles
- Deploying distributed training tasks for deep learning models
- Running large language model inference and fine-tuning
- Managing computational resources through a leasing platform
Alternatives to Cube Studio
- MNN — It delivers high-performance inference and training with a lightweight footprint.
- Together AI — Fast serverless inference and GPU clusters with transparent token pricing.
- DeepInfer Studio — Explore AI inference workflows and resource trade-offs without requiring expensive hardware or GPUs.
- Replicate — Run and fine-tune thousands of open-source and custom AI models via a single cloud API.
- fal — Access 1,000+ generative models and high-performance serverless GPUs.
- AI/ML API — Access over 1000 AI models using one standard OpenAI-compatible API schema.
- Strata — Runs large AI models locally on consumer gaming PCs without server reliance.
- llm-d — Deploys production-grade LLM serving on existing hardware clusters.
- LMDeploy — Accelerates inference with high-performance engines and quantization tools.
- TensorRT — Speeds up inference by 36X compared to CPU-only platforms.
- Union.ai — Runs machine learning tasks natively on Apple Silicon GPUs using Metal.
- SwanLab — Tracks training metrics and system performance with minimal code integration.
All Cube Studio alternatives