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About

How we rank & score

Amazon · Trainium · Layer 2

AWS Trainium 3

Dense training and inference on AWS. Unlike TPU v7 it is designed for both, which makes it the more honest Trainium-vs-TPU comparison.

cloud only Cannot be bought. Exists only inside one cloud, so choosing it is choosing that cloud.

Specifications

Memory
144 GB HBM3e per chip
Bandwidth
4.9 TB/s per chip
Compute
2.52 PFLOPS FP8 per chip
Power
Not published
Interconnect
NeuronLink
Software
AWS Neuron SDK
Form factor
accelerator
Workload
both

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

The catch

AWS-only, and the Neuron SDK is a third software ecosystem to support alongside CUDA and ROCm. Model coverage is the question to ask, not FLOPS.

The economics

Independent analysis has singled out Trainium as the NVIDIA alternative that actually pays off on cost per token — largely because AWS prices it to move.

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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