macrostack

AMD · CDNA 4 · Layer 2

AMD Instinct MI355X

Memory-bound inference. 288 GB against Blackwell's 192 GB is the cleanest technical argument AMD has made in a decade.

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

Specifications

Memory
288 GB HBM3E
Bandwidth
8 TB/s
Compute
~10 PFLOPS sparse FP4
Power
Not consistently published
Interconnect
Infinity Fabric
Software
ROCm
Form factor
accelerator
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, not CUDA. The gap has narrowed sharply but it is still the reason procurement teams say no, and porting cost is real.

The economics

AMD positions this as the best price-per-token part for inference at scale, and claims 2.6x H100 inference throughput on Llama 3.1 405B for the MI350X.

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 cheapest and dearest published on-demand price for an H100 sit 5.6× apart — and the provider, not the chip, is what decides whether you can leave later.

Layer 2.5 — Compute providers · The GPU cost calculator

Compared against

Related silicon

Sources

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