NVIDIA Triton Inference Server vs Paperspace Gradient
NVIDIA Triton Inference Server
developer.nvidia.comPaperspace Gradient
paperspace.comSide by side
| Figure | NVIDIA Triton Inference Server | Paperspace Gradient |
|---|---|---|
| Price from | $375/mo | $8/mo |
| Free plan | Yes | Yes |
| Free trial | Yes | — |
| Open source | — | Yes |
| Web | — | Yes |
| Windows | Yes | Yes |
| macOS | — | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 3 | 17 |
| Spec score · Deep Learning Software | 8.0 (#13) | 8.8 (#3) |
| Frameworks | Supported frameworks include TensorRT, PyTorch, ONNX, OpenVINO, Python, and RAPIDS FIL. | Paperspace says Gradient supports major machine learning frameworks and libraries. |
| Purpose | Dynamo-Triton is open-source inference-serving software for deploying, running, and scaling AI models from multiple frameworks on GPU- or CPU-based infrastructure. | Gradient is a machine learning platform for developing, tracking, and collaborating on machine learning models. |
| Security | NVIDIA's secure-deployment guide says solution security is the deployer's responsibility, dynamic model repository updates are disabled by default, and Triton does not sandbox arbitrary model or backend code. | Paperspace describes centralized permissions and activity logs, and says its security team monitors threats around the clock. |
Plans
NVIDIA Triton Inference Server
- Open-source developmentFree
- NVIDIA AI Enterprise cloud productionPriced on request
- NVIDIA AI Enterprise subscription$4,500 a year
Paperspace Gradient
- Free (Individual)Free
- Pro (Individual)$8 a month
- Growth (Individual)$39 a month
- Free (Team)Free
- Pro (Team)$12 a month
- Growth (Team)$39 a month
- T0Free
- T1$12 a month
- FreeFree
- FreeFree
In their own words
NVIDIA Triton Inference Server
NVIDIA Triton Inference Server is open-source software for deploying and serving AI models on GPU- or CPU-based infrastructure. It supports TensorRT, PyTorch, ONNX, OpenVINO, Python and RAPIDS FIL, with model formats including TensorRT Plan, ONNX, TensorFlow GraphDef and SavedModel, PyTorch TorchScript and PyTorch 2.0. Triton serves real-time, batched, ensemble and audio/video streaming workloads. Dynamic batching and concurrent model execution are among its performance features. Requests can use HTTP/REST, gRPC or the C API, with a Java API for in-process use. Triton integrates with Kubernetes for scaling and Prometheus for monitoring. Deployment options include NVIDIA GPUs, other accelerators, x86 and ARM CPUs, cloud, data centers, edge and embedded systems. NVIDIA lists Linux containers for x86 and Arm, plus Windows and Jetson JetPack binaries. Development code and containers are free; production options include a cloud marketplace plan billed pay as you go and a subscription listed at $4,500 a year per GPU. NVIDIA says deployers are responsible for security, and Triton does not sandbox arbitrary model or backend code.
Paperspace Gradient
Paperspace Gradient is a machine learning platform for building, tracking, and collaborating on models. Its browser-based IDE launches GPU-enabled Jupyter notebooks; teams can share projects, invite collaborators, and connect GitHub to manage code and compute resources. Notebook environments run in Docker containers. For deployment, Gradient serves models through API endpoints, with runtime, instance-type, and autoscaling choices. On-demand GPU and IPU instances are available, and paid instance utilization can cost extra beyond plan fees. Gradient supports major machine learning frameworks and libraries. Plans include free options and paid options listed from $8/mo; individual and team plans have different storage allowances, and notebook plans specify limits on notebooks and running sessions. Gradient is offered for beginners, ML/AI engineers, data scientists, researchers, teams, research groups, and startups. Paperspace also lists a Windows, macOS, and Linux beta desktop app, along with centralized permissions and activity logs.