One stop shop for running AI/ML on AWS
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AWS Deep Learning Containers (DLCs) are pre-built Docker images for running AI/ML workloads on AWS. Each image is tested and patched for security vulnerabilities. For more details, visit our documentation.
- [2026/07/02] vLLM Server v2.1 (AL2023) — EC2:
server-cuda-v2.1· SageMaker:server-sagemaker-cuda-v2.1· vLLM0.24.0; adds JetBrains Mellum2-12B-A2.5B-Thinking (MellumForCausalLM); FlashInfer 0.6.12; drops thetransformers<5.10pin (now requires transformers ≥ 5.5.3). - [2026/07/02] vLLM-Omni v1.4 (AL2023) — EC2:
omni-cuda-v1.4· SageMaker:omni-sagemaker-cuda-v1.4· SageMaker/v1/videosand/v1/videos/syncacceptapplication/jsonagain (JSON→multipart conversion restored); no framework bump (vLLM-Omni 0.21.0rc1). - [2026/07/02] PyTorch v2.12.1 — EC2:
2.12.1-cu130-amzn2023· SageMaker:2.12.1-cu130-amzn2023-sagemaker· Amazon Linux 2023 with EFA, flash-attn, and Transformer Engine; PyTorch 2.12.1 bug-fix release (B200/Triton correctness fixes). - [2026/07/01] vLLM v0.24.0 — EC2:
0.24.0-gpu-py312-ec2· SageMaker:0.24.0-gpu-py312· MiniMax-M3, DiffusionGemma (+CPU), Hierarchical Reasoning Model, OpenMOSS; streaming parser engine (Qwen3, MiniMax-M2, GLM-4.7/5.1/5.2, Nemotron V3); DeepSeek-V4 fixes. - [2026/06/29] SGLang Server v1.1 (AL2023) — EC2:
server-cuda-v1.1· SageMaker:server-sagemaker-cuda-v1.1· SGLang0.5.13; adds NIXL KV connector for prefill/decode disaggregation andrunai-model-streamer[s3,gcs,azure]for fast weight streaming from object storage; starlette CVE patch. - [2026/06/29] SGLang v0.5.14 — EC2:
0.5.14-gpu-py312-ec2· SageMaker:0.5.14-gpu-py312· GLM 5.2, LiquidAI LFM2.5, Kimi-K2.7-Code, DeepSeek V4 on GB300. - [2026/06/14] vLLM v0.23.0 — EC2:
0.23.0-gpu-py312-ec2· SageMaker:0.23.0-gpu-py312· Step-3.7-Flash, Cosmos3 Reasoner, Gemma 4 Unified (encoder-free), Granite Speech Plus, Cohere Mini Code; Anthropic Messages API structured output.
- [2026/04/28] We cannot guarantee security patching on Ubuntu-based vLLM and SGLang images due to the lack of Ubuntu Pro licensing. Customers may continue using these images at their own discretion and risk. We recommend migrating to our Amazon Linux-based images.
- [2026/02/10] Extended support for PyTorch 2.6 Inference containers until June 30, 2026
- PyTorch 2.6 Inference images will continue to receive security patches and updates through end of June 2026
- For complete framework support timelines, see our Support Policy
- Distributed Training on Amazon EKS - Configure and validate a distributed training cluster with DLCs on Amazon EKS.
- DLCs with Amazon SageMaker AI & MLflow - Use DLCs with SageMaker AI managed MLflow for experiment tracking and model management.
- LLM Serving on Amazon EKS with vLLM - Deploy and serve LLMs on Amazon EKS using vLLM DLCs.
- Fine-tuning Meta Llama 3.2 Vision - Fine-tune and deploy Llama 3.2 Vision for web automation using DLCs, Amazon EKS, and Amazon Bedrock.
- DLCs with Amazon Q Developer and MCP - Streamline deep learning environments with Amazon Q Developer and Model Context Protocol.
- LLM Deployment on Amazon EKS - Deploy and optimize LLMs on Amazon EKS using vLLM DLCs. See also: Sample Code
This project is licensed under the Apache-2.0 License.