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How we rank & score

AMD · Instinct MI400 · Layer 2

AMD Helios (Instinct MI455X)

Buyers with a working ROCm story who want more memory per GPU than NVIDIA sells, and a second source at rack scale.

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

Specifications

Memory
31 TB of HBM4 per rack across 72 MI455X GPUs; 432 GB of HBM4 per GPU.
Bandwidth
260 TB/s scale-up per rack; 19.6 TB/s per GPU.
Compute
2.9 exaFLOPS FP4 and 1.4 exaFLOPS FP8 per rack, on AMD's own figures.
Power
Not published per rack.
Interconnect
Scale-up fabric, Helios rack architecture
Software
ROCm
Form factor
rack
Workload
both

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

The catch

ROCm is still the decision, not the silicon. The memory advantage per GPU is real and large — 432 GB against Blackwell-class parts — but it only pays if your stack runs on ROCm without a rewrite, and for most teams today it does not. Racks are quoted around $5-5.5M, which is one of very few public rack prices anywhere at this layer.

The economics

AMD's leverage here is memory capacity and being a second source, not price per FLOP. The commercial proof is commitment rather than benchmark: Oracle Cloud is the first hyperscaler offering a public MI450-series supercluster at 50,000 GPUs from Q3 2026, and OpenAI has committed to 6 GW of AMD Instinct with the first gigawatt in H2 2026.

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

Where you actually rent this

Choosing the part is the easy half. The same accelerator rents for wildly different money depending only on who you rent it from — the H100 spread across published on-demand rates runs about 9x — and the provider, not the chip, is what decides whether you can leave later.

Layer 2.5 — Compute providers · The GPU rental price index

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.

The Macrostack brief

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