Documentation Index
Fetch the complete documentation index at: https://docs.coreweave.com/llms.txt
Use this file to discover all available pages before exploring further.
Any framework that runs on Kubernetes or in Linux containers works on CoreWeave Kubernetes Service (CKS) and SUNK. The following sections highlight popular AI and ML frameworks, grouped by category, with links to CoreWeave guides where available.
Interactive development
The following table lists notebook environments and interactive UIs.
| Framework | Description | CKS guide | SUNK guide |
|---|
| marimo | Reactive notebook environment for interactive Python development with GPU support. | marimo notebooks on CKS | Notebooks on SUNK |
| Jupyter | Interactive computing platform for notebooks, code, and data visualization. | Compatible on CKS | Notebooks on SUNK |
| Open WebUI | Web-based chat interface for interacting with locally deployed language models. | Deploy a model on CKS | Not applicable |
Training frameworks
The following table lists frameworks used for training models and distributed training.
| Framework | Description | CKS guide | SUNK guide |
|---|
| PyTorch | Open-source deep-learning framework with GPU acceleration and distributed training through torchrun. | Compatible on CKS | Submit a training job |
| TensorFlow | Open-source platform for building and deploying machine-learning models across a range of tasks. | Compatible on CKS | Submit a training job |
| Keras | High-level neural network API that runs on top of TensorFlow, JAX, or PyTorch. | Compatible on CKS | Compatible on SUNK |
| JAX | High-performance numerical computing library with automatic differentiation and XLA compilation for GPUs and TPUs. | JAX on marimo notebooks | Compatible on SUNK |
| Hugging Face Transformers | Library for pretrained models for natural language processing, computer vision, and audio tasks. | Compatible on CKS | Compatible on SUNK |
| DeepSpeed | Deep-learning optimization library for distributed training and inference with memory-efficient techniques. | Compatible on CKS | Compatible on SUNK |
| Megatron-LM | NVIDIA framework for training large transformer models using model and data parallelism. | Compatible on CKS | Compatible on SUNK |
| Horovod | Distributed deep-learning training framework supporting TensorFlow, Keras, PyTorch, and Apache MXNet. | Compatible on CKS | Compatible on SUNK |
| PaddlePaddle | Deep-learning framework with support for distributed training and model deployment. | Compatible on CKS | Compatible on SUNK |
| PAX | JAX-based framework for configuring and running ML experiments at scale. | Compatible on CKS | Compatible on SUNK |
| BigDL | Distributed deep-learning library for Apache Spark and Intel hardware. | Compatible on CKS | Compatible on SUNK |
| MegEngine | Deep-learning framework with dynamic and static graph support. | Compatible on CKS | Compatible on SUNK |
| MindSpore | AI computing framework for training and inference across cloud, edge, and device. | Compatible on CKS | Compatible on SUNK |
| torchforge | Training framework for reinforcement learning with group relative policy optimization (GRPO). | Compatible on CKS | torchforge on SUNK |
| veRL | Framework for reinforcement learning training of large language models with Slurm and Ray integration. | Compatible on CKS | veRL on SUNK |
Inference frameworks
The following table lists frameworks used for model serving and inference.
| Framework | Description | CKS guide | SUNK guide |
|---|
| vLLM | High-throughput and memory-efficient LLM inference and serving engine. | Deploy vLLM inference | Compatible on SUNK |
| SGLang | Serving framework for large language models and vision language models. | SGLang on CKS | Compatible on SUNK |
| NVIDIA TensorRT | GPU inference optimizer that delivers low-latency and high-throughput model serving. | Compatible on CKS | Compatible on SUNK |
| NVIDIA TensorRT-LLM | Library for optimizing and deploying large language model inference on GPUs. | TensorRT-LLM on marimo notebooks | Compatible on SUNK |
| NVIDIA NIM | NVIDIA inference microservices for deploying optimized AI models as containerized services. | Deploy NIMs on CKS | Compatible on SUNK |
| NVIDIA Dynamo | Cluster-wide inference orchestration with the Kai scheduler and Grove. | Dynamo inference on CKS | Compatible on SUNK |
| Red Hat AI Inference Stack | GPU-based LLM inference using llm-d, KServe, Istio, and the Gateway API. | Red Hat AI on CKS | Compatible on SUNK |
| OpenVINO | Intel toolkit for optimizing and deploying inference across CPU, GPU, and accelerator hardware. | Compatible on CKS | Compatible on SUNK |
| TensorFlow Lite | Lightweight runtime for running TensorFlow models on edge and mobile devices. | Compatible on CKS | Compatible on SUNK |
Orchestration and management
The following table lists frameworks for scheduling workloads and managing ML operations on clusters.
| Framework | Description | CKS guide | SUNK guide |
|---|
| Ray | Distributed computing framework for scaling AI and Python applications across clusters. | Ray with Kueue | Ray on SUNK |
| Anyscale | Managed platform for deploying and scaling Ray-based distributed AI and ML workloads. | Anyscale on CKS | Compatible on SUNK |
| Kubeflow | Open-source machine-learning platform for portable, scalable ML workflows on Kubernetes. | Kubeflow on CKS | Compatible on SUNK |
| SkyPilot | Framework for running AI and ML workloads across cloud infrastructure. | SkyPilot on CKS | SkyPilot on SUNK |
| Union.ai | Managed platform for Flyte, providing workflow orchestration for data and ML pipelines with a hosted control plane. | Union.ai on CKS | Compatible on SUNK |
| Kueue | Kubernetes-native job queueing system for prioritized workload scheduling and resource management. | Ray with Kueue | Compatible on SUNK |
ML libraries
The following table lists general-purpose machine-learning and AutoML libraries.
| Framework | Description | CKS guide | SUNK guide |
|---|
| XGBoost | Optimized gradient boosting library for classification, regression, and ranking tasks. | Compatible on CKS | Compatible on SUNK |
| scikit-learn | General-purpose machine-learning library for classification, regression, clustering, and preprocessing. | Compatible on CKS | Compatible on SUNK |
| MLlib | Apache Spark’s distributed machine-learning library for classification, regression, clustering, and pipelines. | Compatible on CKS | Compatible on SUNK |
| ML.NET | Cross-platform machine-learning framework for .NET applications. | Compatible on CKS | Compatible on SUNK |
| TPOT | Automated machine-learning tool that optimizes ML pipelines using genetic programming. | Compatible on CKS | Compatible on SUNK |
| AutoKeras | AutoML library built on Keras for automated neural architecture search. | Compatible on CKS | Compatible on SUNK |
| Auto-sklearn | AutoML toolkit that automatically selects and tunes scikit-learn models. | Compatible on CKS | Compatible on SUNK |
| PlaidML | Portable deep-learning backend that runs on a variety of hardware including CPUs and GPUs. | Compatible on CKS | Compatible on SUNK |
GPU acceleration libraries
The following table lists GPU-accelerated computing libraries.
| Framework | Description | CKS guide | SUNK guide |
|---|
| cuDNN | NVIDIA GPU-accelerated library of primitives for deep neural networks. | Compatible on CKS | Compatible on SUNK |
| cuBLAS | NVIDIA GPU-accelerated implementation of the BLAS (Basic Linear Algebra Subprograms) standard. | Compatible on CKS | Compatible on SUNK |
Deprecated frameworks
The following frameworks are deprecated or no longer actively maintained by their upstream projects. They can still run on CKS and SUNK in custom container images.
| Framework | Description | Status |
|---|
| Apache MXNet | Distributed deep-learning framework. | Retired by the Apache Software Foundation in 2023. |
| Caffe and Caffe2 | Deep-learning frameworks for image classification and convolutional networks. | Caffe2 merged into PyTorch. Caffe is no longer actively maintained. |
| Chainer | Deep-learning framework with a define-by-run approach. | Development ended in 2019. Successor: PyTorch. |
| Microsoft Cognitive Toolkit (CNTK) | Deep-learning framework for distributed training. | Archived by Microsoft in 2019. |
| Theano | Numerical computation library with GPU support for defining and optimizing mathematical expressions. | Development ended in 2017. |
| Torch | Scientific computing framework with GPU support based on Lua. | Superseded by PyTorch. |
This list isn’t exhaustive. If a framework isn’t listed, you can build custom container images and deploy them on CKS or SUNK.
