Find edge AI hardware
Task visual wake words · model-size class mobile-class CNN · batch 1 · 17 platforms
Not like-for-like across groups: same model-size class and batch, but 5 different model/precision combinations. Compare within a group; each group is sorted by result.
MobileNetV1 0.25 (MLPerf Tiny VWW) · PTQ (2)
| Platform | Result | Model · precision · stack | Grade · date | Power | Price | Source |
|---|---|---|---|---|---|---|
| Next Generation Snapdragon Mobile Platform MTP | 8753 inferences/s throughput b=1 | MobileNetV1 0.25 (MLPerf Tiny VWW) PTQ · Qualcomm AI Stack | A 2025-09-17 (published) | unknown no power published | unknown | MLPerf Tiny v1.3 (closed) |
| Snapdragon 8 Gen 3 Mobile HDK (Snapdragon 8 Gen 3 Mobile Platform) | 5211 inferences/s throughput b=1 | MobileNetV1 0.25 (MLPerf Tiny VWW) PTQ · Qualcomm AI Stack | A 2024-04-17 (published) | unknown no power published | unknown | MLPerf Tiny v1.2 (closed) |
MobileNetV1 0.25 (MLPerf Tiny VWW) · Uniform symmetric quantization (3)
| Platform | Result | Model · precision · stack | Grade · date | Power | Price | Source |
|---|---|---|---|---|---|---|
| K1_BOARD_V1.0_HIGH_FREQ (K1 Octa-Core RISC-V) | 458 inferences/s throughput b=1 | MobileNetV1 0.25 (MLPerf Tiny VWW) Uniform symmetric quantization · | A 2025-09-17 (published) | unknown no power published | unknown | MLPerf Tiny v1.3 (closed) |
| K1_BOARD_V1.0 (K1 Octa-Core RISC-V) | 225 inferences/s throughput b=1 | MobileNetV1 0.25 (MLPerf Tiny VWW) Uniform symmetric quantization · | A 2025-09-17 (published) | unknown no power published | unknown | MLPerf Tiny v1.3 (closed) |
| LC236R5E176_BOARD_V2.0 (Octopus B1) | 8.31 inferences/s throughput b=1 | MobileNetV1 0.25 (MLPerf Tiny VWW) Uniform symmetric quantization · | A 2024-04-17 (published) | unknown no power published | unknown | MLPerf Tiny v1.2 (closed) |
MobileNetV1 0.25 (MLPerf Tiny VWW) · Uniform scaling from pre-trained weights (1)
| Platform | Result | Model · precision · stack | Grade · date | Power | Price | Source |
|---|---|---|---|---|---|---|
| NDP9120 (N/A) | 244 inferences/s throughput b=1 | MobileNetV1 0.25 (MLPerf Tiny VWW) Uniform scaling from pre-trained weights · N/A | A 2025-09-17 (published) | unknown no power published | unknown | MLPerf Tiny v1.3 (closed) |
MobileNetV1 0.25 (MLPerf Tiny VWW) · INT8 (7)
| Platform | Result | Model · precision · stack | Grade · date | Power | Price | Source |
|---|---|---|---|---|---|---|
| EK-RA8D1 (R7FA8D1AHECBD) | 74.67 inferences/s throughput b=1 | MobileNetV1 0.25 (MLPerf Tiny VWW) INT8 · | A 2024-04-17 (published) | unknown no power published | unknown | MLPerf Tiny v1.2 (closed) |
| NUCLEO-H7A3ZI-Q (STM32H7A3ZIT6Q) | 42.01 inferences/s throughput b=1 | MobileNetV1 0.25 (MLPerf Tiny VWW) INT8 · X-CUBE-AI v9.0.0 | A 2024-04-17 (published) | unknown no power published | unknown | MLPerf Tiny v1.2 (closed) |
| NUCLEO-U3C5ZIT6-Q | 26.90 inferences/s throughput b=1 | MobileNetV1 0.25 (MLPerf Tiny VWW) INT8 · STEDGE-AI Internal version | A 2025-09-17 (published) | unknown no power published | unknown | MLPerf Tiny v1.3 (closed) |
| NUCLEO-U575ZI-Q (STM32U575ZIT6Q) | 16.87 inferences/s throughput b=1 | MobileNetV1 0.25 (MLPerf Tiny VWW) INT8 · X-CUBE-AI v10.2 | A 2025-09-17 (published) | unknown no power published | unknown | MLPerf Tiny v1.3 (closed) |
| NUCLEO-L4R5ZI (STM32L4R5ZIT6U) | 11.24 inferences/s throughput b=1 | MobileNetV1 0.25 (MLPerf Tiny VWW) INT8 · X-CUBE-AI v9.0 | A 2024-04-17 (published) | unknown no power published | unknown | MLPerf Tiny v1.2 (closed) |
| NUCLEO-L4R5ZI-P (STM32L4R5ZIT6P) | 11.18 inferences/s throughput b=1 | MobileNetV1 0.25 (MLPerf Tiny VWW) INT8 · X-CUBE-AI v10.2 | A 2025-09-17 (published) | unknown no power published | unknown | MLPerf Tiny v1.3 (closed) |
| NUCLEO-U385RG-Q (STM32U385RGT6Q) | 10.13 inferences/s throughput b=1 | MobileNetV1 0.25 (MLPerf Tiny VWW) INT8 · X-CUBE-AI v10.2 | A 2025-09-17 (published) | unknown no power published | unknown | MLPerf Tiny v1.3 (closed) |
MobileNetV1 0.25 (MLPerf Tiny VWW) · not stated (4)
| Platform | Result | Model · precision · stack | Grade · date | Power | Price | Source |
|---|---|---|---|---|---|---|
| NUCLEO-H7A3ZI (STM32H7A3ZIT6Q) | 22.85 inferences/s throughput b=1 | MobileNetV1 0.25 (MLPerf Tiny VWW) not stated · Bosch Hardware-Aware Lowering Engine (HALE) version 1.0.175 | A 2024-04-17 (published) | unknown no power published | unknown | MLPerf Tiny v1.2 (closed) |
| DISCO-F746NG (STM32F746NG) | 17.47 inferences/s throughput b=1 | MobileNetV1 0.25 (MLPerf Tiny VWW) not stated · Bosch Hardware-Aware Lowering Engine (HALE) version 1.0.175 | A 2024-04-17 (published) | unknown no power published | unknown | MLPerf Tiny v1.2 (closed) |
| CY8CPROTO-062-4343W (PSoC 62 MCU) | 6.46 inferences/s throughput b=1 | MobileNetV1 0.25 (MLPerf Tiny VWW) not stated · Bosch Hardware-Aware Lowering Engine (HALE) version 1.0.175 | A 2024-04-17 (published) | unknown no power published | unknown | MLPerf Tiny v1.2 (closed) |
| NUCLEO-G0B1RE (STM32G0B1RE) | 0.707 inferences/s throughput b=1 | MobileNetV1 0.25 (MLPerf Tiny VWW) not stated · Bosch Hardware-Aware Lowering Engine (HALE) version 1.0.175 | A 2024-04-17 (published) | unknown no power published | unknown | MLPerf Tiny v1.2 (closed) |
Confidence: A audited MLPerf closed, B documented third-party, C community, D vendor-published, E estimate. Unknown is never assumed. Other like-for-like groups: mobile-class CNN, batch 1 (17)