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SGLang supports direct loading of models from object storage (S3 and Google Cloud Storage) without requiring a full local download. This feature uses the runai_streamer load format to stream model weights directly from cloud storage, significantly reducing startup time and local storage requirements.

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Overview

When loading models from object storage, SGLang uses a two-phase approach:
  1. Metadata Download (once, before process launch): Configuration files and tokenizer files are downloaded to a local cache
  2. Weight Streaming (lazy, during model loading): Model weights are streamed directly from object storage as needed

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Supported Storage Backends

  1. Amazon S3: s3://bucket-name/path/to/model/
  2. Google Cloud Storage: gs://bucket-name/path/to/model/
  3. Azure Blob: az://some-azure-container/path/
  4. S3 compatible: s3://bucket-name/path/to/model/

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Quick Start

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Basic Usage

Simply provide an object storage URI as the model path: 
# S3
python -m sglang.launch_server \
  --model-path s3://my-bucket/models/llama-3-8b/ \
  --load-format runai_streamer

# Google Cloud Storage
python -m sglang.launch_server \
  --model-path gs://my-bucket/models/llama-3-8b/ \
  --load-format runai_streamer
Note: The --load-format runai_streamer is automatically detected when using object storage URIs, so you can omit it: 
python -m sglang.launch_server \
  --model-path s3://my-bucket/models/llama-3-8b/

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With Tensor Parallelism

python -m sglang.launch_server \
  --model-path gs://my-bucket/models/llama-70b/ \
  --tp 4 \
  --model-loader-extra-config '{"distributed": true}'

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Configuration

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Load Format

The runai_streamer load format is specifically designed for object storage, ssd and shared file systems 
python -m sglang.launch_server \
  --model-path s3://bucket/model/ \
  --load-format runai_streamer

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Extended Configuration Parameters

Use --model-loader-extra-config to pass additional configuration as a JSON string: 
python -m sglang.launch_server \
  --model-path s3://bucket/model/ \
  --model-loader-extra-config '{
    "distributed": true,
    "concurrency": 8,
    "memory_limit": 2147483648
  }'

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Available Parameters

ParameterTypeDescriptionDefault
distributedboolEnable distributed streaming for multi-GPU setups. Automatically set to true for object storage paths and cuda alike devices.Auto-detected
concurrencyintNumber of concurrent download streams. Higher values can improve throughput for large models.4
memory_limitintMemory limit (in bytes) for the streaming buffer.System-dependent

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Performance Considerations

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Distributed Streaming

For multi-GPU setups, enable distributed streaming to parallelize weight loading between the processes: 
python -m sglang.launch_server \
  --model-path s3://bucket/model/ \
  --tp 8 \
  --model-loader-extra-config '{"distributed": true}'

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Limitations

  • Supported Formats: Currently only supports .safetensors weight format (recommended format)
  • Supported Device: Distributed streaming is supported on cuda alike devices. Otherwise fallback to non distributed streaming

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See Also