NVIDIA Deepstream vs Lightning LitServe

NVIDIA Deepstream

DeepStream is NVIDIA's platform for building highly optimized video processing pipelines accelerated by NVIDIA's hardware, taking full advantage of TensorRT for accelerated inference and CUDA for parallel processing. It targets many of the same business problems as Inference, including monitoring security cameras, smart cities, and industrial IoT.

DeepStream has a reputation for being difficult to use with a steep learning curve. It requires familiarity with NVIDIA tooling and while it is highly configurable, it's also highly complex. It's focused on video processing, without deep integrations with other tooling. DeepStream is not open source; ensure that the license issuitable for your project.

Choose DeepStream if: you're an expert willing to invest a lot of time and effort into optimizing a single project and high throughput is your primary objective.

Lightning LitServe

LitServe is a lightweight and customizable inference server focused on serving models with minimal overhead. It is fairly minimalistic but flexible and self-contained.

Like Triton, LitServe is task-agnostic, meaning it is designed to balance the needs of vision models with NLP, audio, and tabular models. This means it's not as feature-rich for computer vision applications (for example, it doesn't have any built-in features for streaming video). It is also highly focused on model serving without an abstraction layer like Workflows (offered by Roboflow Inference) for model chaining and integrations with other tools.

Choose LitServe if: you are working on general-purpose machine learningtasks and were previously considering rolling your own server but wanta more featureful starting point.

Make any camera an AI camera with Inference

Inference turns any computer or edge device into a command center for your computer vision projects.

  • 🛠️ Self-host your own fine-tuned models
  • 🧠 Access the latest and greatest foundation models (like Florence-2, CLIP, and SAM2)
  • 🤝 Use Workflows to track, count, time, measure, and visualize
  • 👁️ Combine ML with traditional CV methods (like OCR, Barcode Reading, QR, and template matching)
  • 📈 Monitor, record, and analyze predictions
  • 🎥 Manage cameras and video streams
  • 📬 Send notifications when events happen
  • 🛜 Connect with external systems and APIs
  • 🔗 Extend with your own code and models
  • 🚀 Deploy production systems at scale

Get started today.

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