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SambaNova · RDU · Layer 2

SambaNova SN40L

Serving many large models from one system. The three-tier memory design exists to swap models in and out rather than to hold one resident.

rent Rentable by the hour from multiple clouds; purchasable at scale.

Specifications

Memory
520 MiB SRAM + 64 GiB HBM + up to 1.5 TiB DDR per socket
Bandwidth
Over 1 TB/s DDR-to-HBM model streaming
Compute
Reconfigurable dataflow
Power
Not published
Interconnect
Socket-to-socket fabric
Software
SambaFlow
Form factor
accelerator
Workload
inference

Verified 2026-09-06. Fields reading “not published” are exactly that — we do not estimate a figure a vendor withholds.

The catch

The most unusual architecture here, so the least portable. Independently verified at 1,084 tokens/s for Llama3-8B — but on 16 sockets, which is the number that matters.

The economics

Its argument is models-per-dollar rather than tokens-per-dollar. If you serve one model, this is the wrong shape.

Cost per million tokens is the metric that decides most real purchases, and there is no neutral benchmark for it — every published figure comes from a company selling one side of the comparison. Read all of them, ours included, as claims rather than measurements.

The power question underneath this

A rack of frontier accelerators draws 120–200 kW against a 2026 average of about 27 kW, and the US grid interconnection queue exceeds 2,600 GW with waits approaching five years. Whether you can energise this part is now a harder question than whether you can buy it.

Layer 1 — Energy · The interconnection queue · Rack power density · Tokens per watt

Compared against

Related silicon

Sources

Macrostack does not sell silicon and takes no commission at this layer — there is no affiliate programme for compute, which is exactly why nobody publishes a neutral comparison of it.

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