SambaCloud™

The fastest AI inference on the largest models

Built for speed

Powered by our RDU chip, SambaCloud is the only system to deliver fast inference on the best and largest models. All inference speeds are independently benchmarked and reported by Artificial Analysis.

Built by developers for developers

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SambaNova is the official launch partner for Llama 4.
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Choosing SambaNova —
easy as 1-2-3

Move seamlessly to SambaNova from other providers, including OpenAI.

  1. With the SambaNova OpenAI compatible endpoints, simply set OPENAI_API_KEY to your SambaNova API Key.

  2. Set the base URL.

  3. Choose your model and run!

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FAQs

What is SambaCloud?

SambaCloud is a full-stack AI inference platform developed by SambaNova. It delivers the fastest inference speeds on large open-source models — including Llama, DeepSeek, and Qwen — using SambaNova's proprietary Reconfigurable Dataflow Unit (RDU) AI chip. It is purpose-built for developers who need high-throughput, low-latency AI at scale.

How fast is SambaCloud compared to other AI inference providers?

SambaCloud is independently benchmarked as the fastest AI inference platform for large open-source models. Speeds are reported by Artificial Analysis, a third-party benchmarking organization, making it a verifiable claim rather than a marketing assertion. It consistently outperforms competing cloud inference providers on tokens per second for frontier-scale models.

Which AI models are available on SambaCloud?

SambaCloud supports a range of leading open-source models, including Meta's Llama (SambaNova is the official launch partner for Llama 4), DeepSeek, and Qwen. Models support multiple modalities including text, image, and audio processing, giving developers flexibility across different application types.

What integrations does SambaCloud support?

SambaCloud integrates with a broad set of developer tools and AI frameworks, including CrewAI, Hugging Face, Cline, and AWS. These integrations are designed to help engineering teams accelerate AI development without rearchitecting existing workflows.