Updated model support : You can now import Qwen3 models with model import.

Amazon Bedrock Custom Model Import

You can now import customized open-source models into Amazon Bedrock. This feature allows you to leverage Amazon Bedrock features to make inference calls to your imported models.

Supported Regions

• US East (N. Virginia)
• US East (Ohio)
• US West (Oregon)
• Europe (Frankfurt)

Limitations

• Not supported with: Batch inference, AWS CloudFormation

Supported Model Patterns

• Fine-tuned or Continued Pre-training model
• Adaptation
• Pretrained from scratch

Supported Architectures

• Mistral
• Mixtral
• Flan
• Llama 2, Llama3, Llama3.1, Llama3.2, Llama 3.3, and Mllama
• GPTBigCode
• Qwen2, Qwen2.5, Qwen2-VL, Qwen2.5-VL, Qwen3

Model Import Requirements

• Model Weights: Less than 100GB for multimodal models and 200GB for text models
• Context Length: Less than 128K
• Transformer Version: 4.51.3

Importing a Model from Amazon S3

To import a model, create a model import job in the Amazon Bedrock console or API, specifying the Amazon S3 URI for the model files. The import job automatically detects the model's architecture.

Required Files

• .safetensors - Model weights in Safetensor format
• config.json
• tokenizer_config.json
• tokenizer.json
• tokenizer.model

Supported Tokenizers

• T5Tokenizer
• T5TokenizerFast
• LlamaTokenizer
• LlamaTokenizerFast
• CodeLlamaTokenizer
• CodeLlamaTokenizerFast
• GPT2Tokenizer
• GPT2TokenizerFast
• GPTNeoXTokenizer
• GPTNeoXTokenizerFast
• PreTrainedTokenizer
• PreTrainedTokenizerFast
• Qwen2Tokenizer
• Qwen2TokenizerFast

Source: AWS release notes

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