Vendor: Google
Use Case: AI acceleration for IoT and edge computing
Performance: 4 TOPS (Trillions of Operations Per Second)
Power Consumption: ~2W
Precision: INT8 optimized
Vendor: Intel
Use Case: Computer vision and AI inference
Performance: 1 TOPS
Power Consumption: 1W
Precision: FP16 and INT8
Vendor: Apple
Use Case: AI processing for iPhones, iPads, and Macs
Performance: 35 TOPS (A17 Pro)
Power Consumption: Integrated in SoC, optimized for low power
Precision: Mixed precision (INT8, FP16, FP32)
Vendor: Huawei
Use Case: AI model training and high-performance computing
Performance: 256 TFLOPS (FP16), 512 TOPS (INT8)
Power Consumption: ~310W
Precision: FP16, INT8
Vendor: Qualcomm
Use Case: AI acceleration in Snapdragon mobile chips
Performance: 45 TOPS (Snapdragon 8 Gen 3)
Power Consumption: Integrated in SoC, low power
Precision: Mixed precision (INT4, INT8, FP16)
Vendor: Samsung
Use Case: AI tasks in Samsung Exynos processors
Performance: 40 TOPS (Exynos 2400)
Power Consumption: Integrated in SoC
Precision: INT8, FP16