Power Efficiency Ranking Power Efficiency Ranking    |    Performance vs. Efficiency Tradeoff    |    INT8 Results    |    FP16 Results
Processor AI Accelerator Year Lib Inference Mode INT8,
FPS per Watt		 FP16,
FPS per Watt		 Power Efficiency
Score
Snapdragon 8 EliteHexagon DSP / HTP Gen 42024qh.qhFAST SINGLE ANSWER60.913.2 28.4
Snapdragon 8 Gen 3Hexagon DSP / HTP Gen 32023qh.qhFAST SINGLE ANSWER58.412.8 27.3
Snapdragon 8 Gen 2Hexagon DSP / HTP Gen 22022qh.qhSUSTAINED SPEED56.111.3 25.2
Dimensity 8400NPU 8802024mmFAST SINGLE ANSWER36.612.8 21.6
Dimensity 9300APU 7902023mmFAST SINGLE ANSWER34.412.8 21.0
Dimensity 9400NPU 8902025mmFAST SINGLE ANSWER36.811.7 20.7
Dimensity 8300 UltraAPU 7802023mmFAST SINGLE ANSWER35.511.4 20.1
Snapdragon 888DSP (Hexagon 780) + GPU (Adreno 660)2020qh.qgSUSTAINED SPEED67.14.6 17.6
Snapdragon 8 Gen 1Hexagon DSP / HTP2021qh.qhSUSTAINED SPEED37.47.7 17.0
Dimensity 9200APU 6902022mmSUSTAINED SPEED24.89.2 15.1
Dimensity 9000APU 5902021mmSUSTAINED SPEED21.57.3 12.5
Snapdragon 7 Gen 1Hexagon DSP / HTP2022qh.qhFAST SINGLE ANSWER28.95.3 12.4
Dimensity 800APU 3.0 (4 cores)2020nnSUSTAINED SPEED15.85.2 9.1
Google Tensor G2Google Tensor TPU 2.02022nnSUSTAINED SPEED12.65.1 8.0
Dimensity 820APU 3.0 (4 cores)2020nnSUSTAINED SPEED14.74.4 8.0
Dimensity 1000+APU 3.0 (6 cores)2019nnSUSTAINED SPEED12.14.7 7.5
Google TensorGoogle Tensor TPU2021nnSUSTAINED SPEED74.3 5.5
Snapdragon 865DSP (Hexagon 698) + GPU (Adreno 650)2019hgSUSTAINED SPEED6.12.6 4.0
Snapdragon 855DSP (Hexagon 690) + GPU (Adreno 640)2018hgSUSTAINED SPEED4.92.1 3.2
Exynos 2100GPU (Mali-G78 MP14)2021ggSUSTAINED SPEED2.53 2.7
Kirin 990 5GGPU (Mali-G76 MP10)2019ggSUSTAINED SPEED2.52.6 2.5
Kirin 9000GPU (Mali-G78 MP24)2020ggSUSTAINED SPEED2.42.5 2.4
Snapdragon 845DSP (Hexagon 685) + GPU (Adreno 630)2018hgSUSTAINED SPEED3.61.4 2.2
Snapdragon 710DSP (Hexagon 685) + GPU (Adreno 616)2018hgSUSTAINED SPEED3.31.3 2.1
Kirin 980GPU (Mali-G76 MP10)2018ggSUSTAINED SPEED1.82 1.9
Exynos 9820 OctaGPU (Mali-G76 MP12)2018ggSUSTAINED SPEED1.81.9 1.8

xy  -  This device accelerates quantized [x] and floating-point [y] models using the:


n   -   Android NNAPI

g   -   TensorFlow Lite GPU Delegate  (OpenCL / OpenGL / Metal based)


h     -   Qualcomm Hexagon NN Direct Delegate

qh   -   Qualcomm QNN HTP Delegate

qd   -   Qualcomm QNN DSP Delegate

qg   -   Qualcomm QNN GPU Delegate


e   -   Samsung ENN Delegate

m  -   MediaTek Neuron Delegate

i    -    Apple CoreML Delegate

c   -   TensorFlow Lite / NNAPI default CPU backend


1  -  This SoC might be using unofficial / prototype hardware or drivers

2  -  These are the results of an early prototype. The results of the commercial SoC might be different

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