Espressif
520 KB SRAM and 240 MHz dual-core supports basic ML inference. TFLite Micro and Edge Impulse officially supported.
| Processor | Dual-core Xtensa LX6 @ 240 MHz |
| Cores | 2 |
| Clock | 240 MHz |
| SRAM | 520 KB |
| PSRAM | 4 MB |
| Flash | 16 MB |
| FPU | none |
| Connectivity | Wi-Fi 802.11 b/g/n, Bluetooth 4.2 BR/EDR + BLE |
| Key Features | Hardware crypto acceleration, Ultra-low-power co-processor (ULP) |
| Price | $2–$5 (chip), $5–$15 (dev board) |
136 dev boards available across PlatformIO registries.
Excellent
Espressif's ESP32 excels at anomaly detection via Edge Impulse. The 2-core xtensa-lx6 at 240 MHz with 520 KB SRAM handles 15 KB quantized mo…
Good
The ESP32 runs autoencoder-based anomaly detection with TFLite Micro by learning normal sensor patterns and flagging deviations. Models unde…
Excellent
The ESP32 is an excellent match for fall detection with Edge Impulse. 520 KB SRAM delivers 8.1x the 64 KB minimum while 240 MHz processes 20…
Excellent
The ESP32 is an excellent match for fall detection with TFLite Micro. 520 KB SRAM delivers 8.1x the 64 KB minimum while 240 MHz processes 20…
Excellent
The ESP32 is an excellent match for gesture recognition with Edge Impulse. 520 KB SRAM delivers 8.1x the 64 KB minimum while 240 MHz process…
Excellent
For gesture recognition, the ESP32 with TFLite Micro scores Excellent. Its 520 KB internal SRAM (8.1x the required 64 KB) and 240 MHz clock …
Good
The ESP32 handles image classification effectively with Edge Impulse. 520 KB SRAM at 240 MHz provides 4.1x headroom over the 128 KB requirem…
Good
Running image classification on the ESP32 with TFLite Micro is practical. 520 KB SRAM meets the 128 KB minimum with 4.1x headroom. The 240 M…
Good
Espressif's ESP32 is a solid choice for object detection using Edge Impulse. The xtensa-lx6 core at 240 MHz with 520 KB SRAM accommodates 25…
Good
Espressif's ESP32 is a solid choice for object detection using TFLite Micro. The xtensa-lx6 core at 240 MHz with 520 KB SRAM accommodates 25…
Good
Running people counting on the ESP32 with Edge Impulse is practical. 520 KB SRAM meets the 192 KB minimum with 2.7x headroom. The 240 MHz xt…
Good
The ESP32 handles people counting effectively with TFLite Micro. 520 KB SRAM at 240 MHz provides 2.7x headroom over the 192 KB requirement f…
Good
The ESP32 handles vibration-based predictive maintenance with Edge Impulse by classifying accelerometer patterns into normal, warning, and f…
Excellent
The ESP32 is an excellent match for predictive maintenance with TFLite Micro. 520 KB SRAM delivers 8.1x the 64 KB minimum while 240 MHz proc…
Excellent
The ESP32 is an excellent match for sound classification with Edge Impulse. 520 KB SRAM delivers 8.1x the 64 KB minimum while 240 MHz proces…
Excellent
Espressif's ESP32 excels at sound classification via TFLite Micro. The 2-core xtensa-lx6 at 240 MHz with 520 KB SRAM handles 40 KB quantized…
Excellent
The ESP32 is an excellent match for voice recognition with Edge Impulse. 520 KB SRAM delivers 4.1x the 128 KB minimum while 240 MHz processe…
Excellent
For voice recognition, the ESP32 with TFLite Micro scores Excellent. Its 520 KB internal SRAM (4.1x the required 128 KB) and 240 MHz clock e…
Good
The ESP32 handles wildlife monitoring effectively with Edge Impulse. 520 KB SRAM at 240 MHz provides 4.1x headroom over the 128 KB requireme…
Good
Espressif's ESP32 is a solid choice for wildlife monitoring using TFLite Micro. The xtensa-lx6 core at 240 MHz with 520 KB SRAM accommodates…
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128 KB RAM · 64 MHz
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256 KB RAM · 64 MHz
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512 KB RAM · 200 MHz
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256 KB RAM · 120 MHz
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80 KB RAM · 72 MHz
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640 KB RAM · 250 MHz
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1024 KB RAM · 480 MHz
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128 KB RAM · 80 MHz
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