SambaNova
SambaNova is a disaggregated AI inference platform combining SN50 RDUs, GPUs, and OpenAI‑compatible APIs to deliver fast, energy‑efficient agentic inference at scale. Developers switch across frontier models, bring checkpoints, and operate via SambaOrchestrator with autoscaling, monitoring, and lifecycle control.
Overview
Point existing OpenAI API calls to SambaNova, select a model family, and set throughput targets. SambaOrchestrator provisions capacity on RDUs and GPUs, balances traffic, and monitors latency. Teams iterate by swapping models, bundling prompts, and attaching checkpoints without re‑wiring services or retraining pipelines.
Capabilities built for premium, scalable inference
Best suited for engineering teams building assistants, coding tools, retrieval‑augmented applications, and AI agents that must run quickly and economically at scale. Cloud platforms, SaaS providers, and enterprise IT can standardize on one inference layer while retaining model choice and data‑center control. Governments and regulated sectors benefit from sovereign deployments that keep data within national boundaries without sacrificing performance.
- OpenAI‑compatible APIs let teams migrate workloads by changing only endpoint configuration.
- Run Llama, DeepSeek, MiniMax, and gpt‑oss‑120b with consistent, predictable latency.
- Autoscaling and load balancing keep throughput steady across RDUs, GPUs, and racks.
- Bring your own checkpoints to host private or fine‑tuned enterprise models.
- Dataflow architecture and tiered memory maximize tokens per watt for agents.
Why it stands out
Who should use SambaNova
Getting started is simple: create an account, generate an API key, and swap your OpenAI base URL for SambaNova’s endpoint. Most applications work without SDK changes. Use SambaOrchestrator to define model bundles, autoscaling policies, and routing rules, then monitor throughput and latency from a single console. Bring your own checkpoints to deploy internal models, or select from supported frontier families. Deployment spans from a single SambaRack node to multi‑rack capacity or partner sovereign facilities, with the same API contract. Documentation, examples, and an early‑access developer program accelerate onboarding.
Premium inference pairs the right silicon with the right model, then scales it efficiently across data centers.
Getting started
SambaNova consolidates hardware and software into a practical inference layer for agentic AI. SN50 RDUs, model bundling, and OpenAI‑compatible APIs cut latency and cost while preserving flexibility across models and data centers. With autoscaling, monitoring, and BYO checkpoints built in, teams move from prototype to production quickly and operate predictably at scale.
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SambaNova
SambaNova, Inc. builds integrated AI systems combining custom silicon, systems software, and data‑center solutions for high‑performance inference. The company’s RDU architecture focuses on dataflow execution and efficient memory hierarchies, enabling enterprises and governments to run state‑of‑the‑art models with better performance‑per‑watt and flexible deployment across owned, managed, or sovereign facilities.
SambaNova delivers premium AI inference by pairing fifth‑generation SN50 Reconfigurable Dataflow Units with GPUs and a software stack built for agent‑centric workloads. Its dataflow architecture, tiered memory, and model bundling maximize tokens per watt while sustaining high throughput for complex, multi‑agent pipelines. Developers access models through OpenAI‑compatible endpoints, switch between frontier families such as Llama, DeepSeek, and MiniMax, and run OpenAI’s gpt‑oss‑120b where low latency is paramount. SambaStack orchestrates deployments across SambaRack systems and partner sovereign data centers, with autoscaling, load balancing, monitoring, and model management included. Teams can bring their own checkpoints, operate mixed fleets, and scale from a single node to rack‑level capacity without re‑architecting applications. The result is fast, cost‑efficient inference that preserves flexibility: deploy on RDUs for efficiency, burst on GPUs for elasticity, and coordinate both for disaggregated agentic pipelines. Enterprises use SambaNova to deliver near real‑time assistants, coding agents, and knowledge tools while retaining control over performance, spend, and data locality.
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