To protect proprietary data and intellectual property, nations and large corporations are increasingly training their own "national models" from scratch. This move away from reliance on global, US-based models creates a significant market for on-prem and private cloud infrastructure that ensures data privacy and security.
Mature enterprises are moving beyond using AI for operational efficiency. They are now leveraging their unique, proprietary data to train custom models. This allows them to build differentiated services and products that competitors cannot replicate, creating new top-line revenue opportunities rather than just improving bottom-line savings.
SambaNova defines "premium inference" along two axes: running the largest models for maximum accuracy and doing so with low latency. This contrasts with services that achieve speed by only running smaller, less accurate models or by quantizing larger ones, which sacrifices precision.
A 2-second delay is acceptable for a single user prompt. However, in an agentic system where 20 agents communicate sequentially, that delay compounds to 40 seconds, rendering the application unusable. This shift necessitates infrastructure with sub-second response times, driving hardware deployment to urban centers.
The need for low-latency services for agents and real-time applications in finance and healthcare is driving a shift towards distributed data centers. Instead of remote gigawatt facilities, companies are deploying smaller, power-efficient, air-cooled racks like SambaNova's in existing metropolitan data centers, closer to users.
SambaNova's SN40 rack outperforms a 140-kilowatt NVIDIA GPU rack with just 10 kilowatts and air cooling. This allows running trillion-parameter models in a single rack, dramatically reducing footprint, power consumption, and the need for specialized liquid-cooled data centers.
When all cloud providers offer the same NVIDIA hardware, they are forced to compete on price, eroding margins. By integrating specialized hardware like SambaNova's, they can offer premium, differentiated services—such as faster inference on larger models—allowing them to charge more and improve overall business economics.
Partnering with companies like Armada, SambaNova deploys its power-efficient 10-kilowatt racks inside modular shipping containers. This enables advanced AI inference for critical, remote operations such as oil rigs and military deployments, where building a traditional data center is impossible.
The CEO of SambaNova describes the current AI infrastructure market—from hyperscalers to sovereign clouds—as a "land grab." The primary focus is on rapidly scaling to acquire users and customers, as historical tech cycles show that the first large-scale players often establish enduring market dominance.