The custom MI450-based accelerator is not a product available on the open market. It is a co-engineered variant purpose-built for Meta's internal workloads. According to SemiAnalysis, the chip uses AMD's chiplet architecture to create a version with significantly reduced compute and memory resources, tuned specifically for the memory-bandwidth-per-dollar ratio that recommendation systems demand .
Meta's reasoning, as reported, is to optimize CPU-to-GPU compute ratios at the rack level and improve memory bandwidth cost-efficiency for its RecSys (recommendation system) workloads, which run billions of inferences per day .
| Specification | Standard AMD Instinct MI455X | Meta Custom Variant | Difference |
|---|---|---|---|
| Compute chiplets | 8 (on TSMC N2) | 4 | 50% fewer |
| HBM4 stacks and total memory | 12 × 36 GB (12‑Hi) = 432 GB | 6 × 24 GB (8‑Hi) = 144 GB | ~67% less memory |
| Total memory bandwidth | ~19.6 TB/s | Reduced proportionally | Significantly lower |
The standard Instinct MI455X, which powers AMD's Helios rack-scale system, is an engineering flagship built on the CDNA 5 architecture. It uses 8 compute chiplets on TSMC's N2 (2nm) process and 12 HBM4 12-Hi stacks to deliver 432 GB of memory . Meta's custom version cuts the compute dies in half—down to 4—and drops to 6 HBM4 8-Hi stacks, yielding only 144 GB of memory . This is essentially half the compute silicon and one-third of the memory bandwidth of the fully-fledged MI455X.
Because the chip uses fewer chiplets and HBM stacks, Meta's variant is also physically smaller and uses less power and packaging complexity, reducing cost per accelerator .
SemiAnalysis levied several sharp criticisms at Meta's decision:
The core complaint is that by stripping down the chip, Meta sacrifices versatility and future-proofing for narrow near-term cost optimization, potentially locking itself out of more capable hardware needed for frontier AI workloads .
Not all observers agree. Some defense of the approach notes that recommendation systems do not need frontier LLM capacity. What they need is bandwidth per dollar on a task run billions of times a day, making the cut-down chip a rational specialization rather than a mistake .
On February 24, 2026, Meta and AMD announced a five-year, $60 billion strategic partnership to deploy up to 6 gigawatts of AMD Instinct GPUs for Meta's AI infrastructure . Key terms include:
The custom "Half-MI450" is the first concrete product manifestation of this megadeal: a chip tailored specifically to Meta's recommendation inference needs, designed to maximize cost- and power-efficiency per inference at massive rack-level scale, exactly what the $60 billion partnership was structured to enable .