# Amazon SageMaker Inference vs TorchServe

| Attribute | Amazon SageMaker Inference | TorchServe |
|---|---|---|
| **Vioscale score** | 36.1 (40% (low)) | 63.3 (28% (low)) |
| activity.commits_last_30d | - | 100 |
| adoption.dependent_repos | - | 92,053 |
| adoption.github_stars | - | 102,599 |
| deployment.options | `{"cloud":true}` | `{"cloud":true,"self_hosted":true}` |
| description.long | AWS SageMaker Inference is a managed service for deploying trained machine learning models into production, supporting multiple ML frameworks and providing integration with AWS MLOps tools like model registries, feature stores, and CI/CD pipelines. | TorchServe enables efficient production deployment of machine learning models at scale across different cloud platforms and infrastructure. It supports multi-model serving, provides monitoring and logging capabilities, and offers REST API endpoints for application integration. |
| features.capabilities | `{"gpu_acceleration":true,"multi_model_serving":true,"multi_framework_support":true,"autoscaling_scale_to_zero":true}` | - |
| integrations.count | 13 | 6 |
| integrations.list | `[{"name":"TensorFlow"},{"name":"PyTorch"},{"name":"ONNX"},{"name":"XGBoost"},{"name":"SageMaker Pipelines"},{"name":"SageMaker Projects"},{"name":"SageMaker Feature Store"},{"name":"SageMaker Model Registry"},{"name":"SageMaker Clarify"},{"name":"Amazon Bedrock"},{"name":"Amazon S3"},{"name":"AWS CloudWatch"},{"name":"AWS CloudTrail"}]` | `[{"name":"AWS Inferentia2"},{"name":"AWS SageMaker"},{"name":"Google Cloud Vertex AI"},{"name":"Google Cloud TPUv5"},{"name":"Intel oneAPI"},{"name":"Datadog"}]` |
| language.primary | - | Python |
| market.availability | `{"hqCountry":"US","primaryMarkets":["US"],"availabilityScope":"global","availableCountries":["US"],"notAvailableCountries":[]}` | - |
| platform.support | `{"cli":true,"web":true}` | `{"cli":true,"linux":true,"windows":true}` |
| pricing | - | `{"type":"open_source","sourceUrl":"https://pytorch.org/serve/","retrievedAt":"2026-08-20T16:35:31.436Z"}` |
| pricing.free_tier | yes | - |
| pricing.model | - | open_source |
| pricing.price_level | - | free |
| release.cadence_days | - | 42 |
| release.history | - | `[{"url":"https://github.com/pytorch/pytorch/releases/tag/v2.13.0","date":"2026-07-08T17:39:58Z","type":"stable","version":"v2.13.0"},{"url":"https://github.com/pytorch/pytorch/releases/tag/v2.12.1","date":"2026-06-18T00:41:17Z","type":"stable","version":"v2.12.1"},{"url":"https://github.com/pytorch/pytorch/releases/tag/v2.12.0","date":"2026-05-13T17:38:06Z","type":"stable","version":"v2.12.0"},{"url":"https://github.com/pytorch/pytorch/releases/tag/v2.11.0","date":"2026-03-23T18:38:28Z","type":"stable","version":"v2.11.0"},{"url":"https://github.com/pytorch/pytorch/releases/tag/v2.10.0","date":"2026-01-21T17:05:16Z","type":"stable","version":"v2.10.0"},{"url":"https://github.com/pytorch/pytorch/releases/tag/v2.9.1","date":"2025-11-12T19:27:19Z","type":"stable","version":"v2.9.1"},{"url":"https://github.com/pytorch/pytorch/releases/tag/v2.9.0","date":"2025-10-15T17:12:27Z","type":"stable","version":"v2.9.0"},{"url":"https://github.com/pytorch/pytorch/releases/tag/v2.8.0","date":"2025-08-06T17:06:10Z","type":"stable","version":"v2.8.0"},{"url":"https://github.com/pytorch/pytorch/releases/tag/v2.7.1","date":"2025-06-04T18:13:15Z","type":"stable","version":"v2.7.1"},{"url":"https://github.com/pytorch/pytorch/releases/tag/v2.7.0","date":"2025-04-23T16:16:06Z","type":"stable","version":"v2.7.0"},{"url":"https://github.com/pytorch/pytorch/releases/tag/v2.6.0","date":"2025-01-29T17:18:54Z","type":"stable","version":"v2.6.0"},{"url":"https://github.com/pytorch/pytorch/releases/tag/v2.5.1","date":"2024-10-29T17:58:24Z","type":"stable","version":"v2.5.1"},{"url":"https://github.com/pytorch/pytorch/releases/tag/v2.5.0","date":"2024-10-17T16:26:53Z","type":"stable","version":"v2.5.0"},{"url":"https://github.com/pytorch/pytorch/releases/tag/v2.4.1","date":"2024-09-04T19:59:29Z","type":"stable","version":"v2.4.1"},{"url":"https://github.com/pytorch/pytorch/releases/tag/v2.4.0","date":"2024-07-24T18:39:28Z","type":"stable","version":"v2.4.0"},{"url":"https://github.com/pytorch/pytorch/releases/tag/v2.3.1","date":"2024-06-05T19:16:07Z","type":"stable","version":"v2.3.1"},{"url":"https://github.com/pytorch/pytorch/releases/tag/v2.3.0","date":"2024-04-24T16:12:17Z","type":"stable","version":"v2.3.0"},{"url":"https://github.com/pytorch/pytorch/releases/tag/v2.2.2","date":"2024-03-27T22:27:02Z","type":"stable","version":"v2.2.2"},{"url":"https://github.com/pytorch/pytorch/releases/tag/v2.2.1","date":"2024-02-22T21:15:00Z","type":"stable","version":"v2.2.1"},{"url":"https://github.com/pytorch/pytorch/releases/tag/v2.2.0","date":"2024-01-30T17:58:51Z","type":"stable","version":"v2.2.0"}]` |
| security.fedramp | yes | - |
| security.gdpr | yes | - |
| security.hipaa | yes | - |
| security.pci | yes | - |
| security.scorecard | - | 6.4 |
| security.vulnerabilities | - | `{"count":13,"source":"https://advisories.ecosyste.ms/api/v1/advisories?ecosystem=pypi&package_name=torch&per_page=100","last_12m":0,"max_severity":"CRITICAL"}` |

## Capabilities (Model Serving)

| Capability | Amazon SageMaker Inference | TorchServe |
|---|:--:|:--:|
| **Capabilities** |  |  |
| Continuous batching | - | - |
| Dynamic batching | - | - |
| Multi framework support | ✓ | - |
| GPU acceleration | ✓ | - |
| Multi GPU multi node | - | - |
| Quantization support | - | - |
| Openai compatible API | - | - |
| Autoscaling scale to zero | ✓ | - |
| Multi model serving | ✓ | - |
| Canary ab rollout | - | - |
| Kubernetes native | - | - |
| Open source | - | - |

*Source: Vioscale. Generated 2026-09-01T14:44:39.389Z. "-" = undocumented, not absent.*