Triton Inference Server
by NVIDIA · free · Last verified 2026-03-17
Triton is an open-source inference server from NVIDIA designed for high-performance, production-ready AI. It supports deploying models from virtually any framework, such as TensorFlow, PyTorch, and ONNX, on both GPUs and CPUs. Key features include dynamic batching, concurrent model execution, and model ensembling to maximize throughput and resource utilization.
https://developer.nvidia.com/triton-inference-server ↗C+
C+—Average
Adoption: BQuality: AFreshness: ACitations: BEngagement: F
Specifications
- License
- BSD-3-Clause
- Pricing
- free
- Capabilities
- Multi-framework model serving (TensorFlow, PyTorch, ONNX, TensorRT), Dynamic batching to increase throughput, Concurrent model execution on single or multiple GPUs, Model ensembling for complex inference pipelines, HTTP/gRPC and C API endpoints, Real-time performance and utilization metrics, Support for custom backends and pre/post-processing logic, Model versioning and management, Optimized for NVIDIA GPUs and TensorRT
- Integrations
- Kubernetes, Prometheus, Grafana, Docker, Kubeflow, MLflow, AWS SageMaker, Google Vertex AI, Azure Machine Learning
- Use Cases
- [object Object], [object Object], [object Object], [object Object], [object Object]
- API Available
- Yes
- SDK Languages
- python, cpp, java
- Deployment
- self-hosted, docker, kubernetes
- Rate Limits
- N/A (self-hosted)
- Data Privacy
- Self-hosted, user-managed
- Tags
- model-serving, inference-server, nvidia, gpu, mlops, production-ai, multi-framework, open-source, high-performance, deep-learning, enterprise
- Added
- 2026-03-17
- Completeness
- 0.85%
Index Score
59.1Adoption
65
Quality
88
Freshness
82
Citations
62
Engagement
0