Meta MTIA 450

MTIA 450 doubles MTIA 400's HBM bandwidth to 18.4 TB/s and lifts MX4 compute 75% for generative AI inference. Meta schedules it for mass deployment in early 2027. Sources and verification dates.

Owner Meta Status Announced US platform

Verified

Open the primary source Compare side by side

Every published figure

Source per value
Owner The company that specified the chip and runs it in its own cloud, data centers or products.
Meta 1
Role What the owner says the chip is for: training, inference, both, or a general-purpose server CPU.
Inference 1
Design partner The ASIC house that co-designed or physically implemented the chip (Broadcom, Marvell, MediaTek, Alchip, GUC and others), as stated by the owner, the partner, a filing or named trade-press reporting. 'In-house' when the owner states it designed the chip itself, including through an acquired team such as Annapurna Labs.
Broadcom 1
Partner basis Who says so: the owner, the partner, or press reporting with the outlet named. A reported partner is not confirmed by the owner.
Stated by Meta: developed in close partnership with Broadcom. 1
Memory On-package memory type (HBM2e, HBM3, HBM3E, LPDDR5) or, for CPUs, the memory the socket drives (DDR5).
HBM 1
Memory capacity GB On-package memory per chip in GB. Blank for CPUs, whose memory sits off-package.
288 1
Memory bandwidth TB/s Peak memory bandwidth per chip in TB/s, as published.
18.4 1
BF16 TFLOPS Published BF16 throughput per chip or accelerator module in TFLOPS. FP16 is a separate column. See the precision note for sparsity and module scope.
3,500 1
MX8 TFLOPS Published MX8 throughput per chip or accelerator module in TFLOPS. See the precision note for shared-format figures, sparsity and module scope.
7,000 1
MX4 TFLOPS Published MX4 throughput per chip or accelerator module in TFLOPS. See the precision note for shared-format figures, sparsity and module scope.
21,000 1
Precision note What the throughput figures mean: dense or sparse, which precision, per chip or per package, and any figure the owner states only in another unit.
Meta's chip-specifications image: 3500 BF16 TFLOPS, 7000 TFLOPS in its shared FP8/MX8 row, 21000 MX4 TFLOPS, per accelerator module. The shared FP8/MX8 figure is kept in the MX8 column and labelled here; Meta does not label sparsity. Module TDP 1400 W. 1
Power W Chip or package power in watts as published (TDP, TBP or typical power; the source says which).
1,400 1
Largest pod chips The largest scale-up domain the owner states: chips per pod, UltraServer, supernode or rack joined by the chip-to-chip interconnect.
72 1
Status Announced: public roadmap without verified deployment. Sampling: first silicon or limited internal use. Preview: customers can request early access, without a GA claim. Deployed: stated production use or general availability. Discontinued: program stopped.
Announced 1
Announced Year the owner first announced the chip publicly.
2,026 1
Deployment scale The largest deployment the owner or a named report states: chip counts, clusters, gigawatts or regions.
Scheduled for mass deployment in early 2027 (Meta) 1
How to get it How an outside buyer can use the chip: a named cloud instance or service, a product, or 'Internal only'.
Internal only 1

Not verified in the sources reviewed: foundry, node, fp16, mxfp8, mxfp4, fp8, int8, fp4.

Sources

  1. Meta AI: MTIA: scaling AI chips for billions accessed 2026-11-11
  2. ServeTheHome: Meta outlines new MTIA accelerator roadmap for its next-gen AI compute mix accessed 2026-11-11