Captive silicon. MTIA is designed by Meta for its own data centers and cannot be bought or rented from anyone, and no cloud provider offers it, so there is no rental price for this part. MTIA 450 is not yet shipping: Meta states it is scheduled for mass deployment in early 2027, so these figures are Meta's stated targets for a part that has not entered volume production.
Meta logo

Meta MTIA 450

Type: ASICArchitecture: MTIAExpected: 2027Status: Announced, not shippingSpec confidence: Official
FP8 (dense)
7,000
TFLOPS
Memory
288 GB
HBM
Bandwidth
18.4 TB/s
memory
TDP
1.4 kW

Overview

The Meta MTIA 450 is a generative AI inference specialist, and the point where Meta stopped optimising for balance and went after decode throughput. Meta doubled HBM bandwidth from the MTIA 400 to 18.4 TB/s, which it describes as much higher than existing leading commercial products, because memory bandwidth is the factor that most limits generative AI inference performance. HBM capacity stays at 288 GB and module power rises to 1400 W. Compute reaches 21 PFLOPS of MX4, 7 PFLOPS of FP8 and 3.5 PFLOPS of BF16, an increase of 75 percent in MX4 throughput over the MTIA 400. Beyond raw numbers Meta added hardware acceleration aimed at specific inference bottlenecks, easing Softmax and FlashAttention pressure and speeding up mixture-of-experts feed-forward network computation. It also supports mixed low-precision computation without the software overhead that data type conversion normally imposes, and introduces custom Meta data types intended to raise throughput while preserving model quality at minimal cost in chip area. Meta frames the balance plainly: the part delivers six times the MX4 throughput of its own FP16 and BF16, which is a statement about how far inference has moved toward low precision.

Performance

Peak theoretical throughput by precision type

PrecisionPeak
FP64
No verified data available
FP32
No verified data available
TF32
No verified data available
BF16
Brain Float 16
3,500TFLOPS
FP16
No verified data available
FP8
8-bit floating point
7,000TFLOPS
FP6
No verified data available
FP4
4-bit floating point
21,000TFLOPS
INT8
No verified data available

Specifications

Architecture

MTIA

Form Factor

No verified data available

Launch Year

2027

Process Node

No verified data available

Memory

288 GB HBM

Bandwidth

18,400 GB/s

TDP

1.4 kW

Max power (Flopper estimate)

~1.6 kW est. Flopper estimate: 1400 W TDP x 1.15. The vendor publishes no maximum board power for this part.

Interconnect

2.4 TB/s

direction and scope not stated by vendor

Spec Confidence

Official

Full Specifications

Memory
Memory 288 GB
Memory Type HBM
Bandwidth 18.4 TB/s
Interface Width No verified data available
Interconnect & I/O
Interconnect Bandwidth 2.4 TB/s direction and scope not stated by vendor
Power & Thermal
TDP 1.4 kW
Max power (Flopper estimate) ~1.6 kW est.
Enterprise Features
Compute APIs PyTorch, Triton
General
Form Factor No verified data available
Architecture MTIA
Process Node No verified data available
Launch Year 2027

Datasheet & Resources

Data Provenance

Every figure traced to a source

Data Quality

Spec confidence
Official
Clock basis
Boost
Core precisions with figures
3 of 9
Normalization
All values in TFLOPS

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Frequently Asked Questions

How many TFLOPS does the Meta MTIA 450 have?

The Meta MTIA 450 delivers 7,000 TFLOPS FP8 at peak. Flopper does not currently have verified FP32 and FP16 throughput figures for it.

What is the power consumption of the Meta MTIA 450?

The Meta MTIA 450 has a TDP (Thermal Design Power) rating of 1,400 watts.

How much memory does the Meta MTIA 450 have?

The Meta MTIA 450 is equipped with 288 GB of memory with 18,400 GB/s of memory bandwidth.

What architecture is the Meta MTIA 450 based on?

The Meta MTIA 450 is based on the MTIA architecture, launched in 2027.

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