# Amazon SageMaker Inference vs SGLang

**Leader by vioscaleAI score:** Amazon SageMaker Inference

| Attribute | Amazon SageMaker Inference | SGLang |
|---|---|---|
| **vioscaleAI score** | 67.6 (75% (high)) | 50.4 (10% (low)) |
| content.faq | `[{"answer":"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. It is indexed under Model Serving.","source":"https://aws.amazon.com/ec2/pricing/?nc2=h_pr_ec2","question":"What is Amazon SageMaker Inference?","confidence":0.6},{"answer":"Amazon SageMaker Inference offers a free tier, so you can start without paying. Pricing changes often, so verify at source before relying on it.","source":"https://aws.amazon.com/bedrock/pricing/?nc2=h_pr_br","question":"Is Amazon SageMaker Inference free?","confidence":0.6},{"answer":"Amazon SageMaker Inference supports the web and a command-line interface. Platforms we have not confirmed are simply not listed here rather than ruled out.","source":"https://aws.amazon.com/ec2/pricing/?nc2=h_pr_ec2","question":"What platforms does Amazon SageMaker Inference support?","confidence":0.6},{"answer":"We have only confirmed a cloud / SaaS deployment for Amazon SageMaker Inference, so it appears to be vendor-hosted. If a self-hosted option exists we have not found it documented publicly.","source":"https://aws.amazon.com/ec2/pricing/?nc2=h_pr_ec2","question":"Can Amazon SageMaker Inference be self-hosted?","confidence":0.6},{"answer":"We have confirmed 15 integrations for Amazon SageMaker Inference, including TensorFlow, PyTorch, ONNX, XGBoost, SageMaker Pipelines, SageMaker Projects, SageMaker Feature Store and SageMaker Model Registry, plus 7 more. This is what we could verify from public sources, so the vendor may support others we have not indexed.","source":"https://aws.amazon.com/bedrock/pricing/?nc2=h_pr_br","question":"What does Amazon SageMaker Inference integrate with?","confidence":0.6},{"answer":"We have independently confirmed HIPAA and GDPR for Amazon SageMaker Inference. Certifications we do not list are ones we have not been able to verify from public sources, which is not the same as Amazon SageMaker Inference not holding them. Always confirm compliance directly before you rely on it.","source":"https://aws.amazon.com/compliance/?nc2=h_dsc_aa_cmp","question":"What security certifications does Amazon SageMaker Inference have?","confidence":0.7},{"answer":"Amazon SageMaker Inference is available worldwide. Its primary market is the United States.","source":"https://aws.amazon.com/bedrock/pricing/?nc2=h_pr_br","question":"Where is Amazon SageMaker Inference available?","confidence":0.5}]` | `[{"answer":"An open-source inference system designed for production deployments of large language and multimodal models, supporting both single-GPU and distributed cluster setups with emphasis on low latency and high throughput. It is indexed under Model Serving.","source":"https://sgl-project.github.io/","question":"What is SGLang?","confidence":0.6},{"answer":"SGLang is open source, so it can be self-hosted and used at no licence cost. Pricing changes often, so verify at source before relying on it.","source":"https://sgl-project.github.io/","question":"Is SGLang free to use?","confidence":0.6},{"answer":"Yes. SGLang can be deployed self-hosted, so it does not have to run on the vendor's infrastructure.","source":"https://sgl-project.github.io/","question":"Can SGLang be self-hosted?","confidence":0.6}]` |
| deployment.options | `{"cloud":true}` | `{"self_hosted":true}` |
| description.long | A managed inference service that deploys machine learning models with support for various frameworks and deployment patterns, ranging from low-latency millisecond responses to high-throughput scenarios, with integration into MLOps workflows. | An open-source inference system designed for production deployments of large language and multimodal models, supporting both single-GPU and distributed cluster setups with emphasis on low latency and high throughput. |
| features.capabilities | `{"gpu_acceleration":true,"multi_model_serving":true,"multi_framework_support":true,"autoscaling_scale_to_zero":true}` | `{"open_source":true,"gpu_acceleration":true,"multi_gpu_multi_node":true,"openai_compatible_api":true,"multi_framework_support":true}` |
| integrations.count | 13 | 3 |
| 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":"S3","native":true,"direction":"inbound"},{"name":"SharePoint","native":true,"direction":"inbound"},{"name":"Confluence","native":true,"direction":"inbound"}]` | `[{"name":"Hugging Face"},{"name":"OpenAI"},{"name":"Slack","native":false}]` |
| market.availability | `{"primaryMarkets":["US"],"availabilityScope":"global","availableCountries":[],"notAvailableCountries":[]}` | - |
| platform.support | `{"cli":true,"web":true}` | - |
| pricing | `{"type":"usage","summary":"Pay-as-you-go usage pricing. New AWS customers receive up to $200 in Free Tier credits; free tier available for 6 months.","currency":"USD","freeTier":true,"sourceUrl":"https://aws.amazon.com/s3/pricing/?nc2=h_pr_s3","retrievedAt":"2026-09-29T15:03:46.730Z"}` | `{"type":"open_source","sourceUrl":"https://sgl-project.github.io/","retrievedAt":"2026-09-06T13:46:39.277Z"}` |
| pricing.free_tier | yes | - |
| pricing.model | freemium | open_source |
| pricing.price_level | low | free |
| pricing.transparent | no | - |
| security.fedramp | yes | - |
| security.gdpr | yes | - |
| security.hipaa | yes | - |
| security.iso27001 | yes | - |
| security.pci | yes | - |
| security.soc2 | yes | - |
| security.trust_center | https://aws.amazon.com/security/?nc1=f_cc | - |

## Capabilities (Model Serving)

| Capability | Amazon SageMaker Inference | SGLang |
|---|:--:|:--:|
| **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: vioscaleAI. Generated 2026-10-16T20:39:21.470Z. "-" = undocumented, not absent.*