Espressif
ESP32-S3 Edge AI Guides
512 KB SRAM with vector SIMD instructions makes this the best Espressif chip for ML inference. Native camera interface enables vision workloads.
Hardware Specs
| Processor | Dual-core Xtensa LX7 @ 240 MHz |
| Cores | 2 |
| Clock | 240 MHz |
| SRAM | 512 KB |
| PSRAM | 8 MB |
| Flash | 16 MB |
| FPU | none |
| Connectivity | Wi-Fi 802.11 b/g/n, Bluetooth 5.0 LE |
| Key Features | Vector instructions (SIMD), USB OTG, LCD/Camera interface, Up to 8 MB PSRAM |
| Price | $3–$8 (chip), $10–$25 (dev board) |
Dev Boards in This Family
57 edge-AI-capable ESP32-S3 development boards with specs and compatibility details.
unPhone 9
University of Sheffield
8512 KB RAM · 240 MHz
unPhone 8
University of Sheffield
2368 KB RAM · 240 MHz
4D Systems GEN4-ESP32 16MB (ESP32S3-R8N16)
4D Systems
320 KB RAM · 240 MHz
Adafruit pyCamera S3
Adafruit
320 KB RAM · 240 MHz
Adafruit Feather ESP32-S3 2MB PSRAM
Adafruit
320 KB RAM · 240 MHz
Adafruit Feather ESP32-S3 No PSRAM
Adafruit
320 KB RAM · 240 MHz
Adafruit Feather ESP32-S3 Reverse TFT
Adafruit
320 KB RAM · 240 MHz
Adafruit Feather ESP32-S3 TFT
Adafruit
320 KB RAM · 240 MHz
Adafruit MatrixPortal ESP32-S3
Adafruit
320 KB RAM · 240 MHz
Adafruit Metro ESP32-S3
Adafruit
320 KB RAM · 240 MHz
Adafruit QT Py ESP32-S3 (4M Flash 2M PSRAM)
Adafruit
320 KB RAM · 240 MHz
Adafruit QT Py ESP32-S3 No PSRAM
Adafruit
320 KB RAM · 240 MHz
Hardware Guides
ESP32-S3 Anomaly Detection with Edge Impulse
Espressif's ESP32-S3 excels at anomaly detection via Edge Impulse. The 2-core xtensa-lx7 at 240 MHz with 512 KB SRAM handles 15 KB quantized…
ESP32-S3 Anomaly Detection with TFLite Micro
For anomaly detection, the ESP32-S3 with TFLite Micro scores Excellent. Its 512 KB internal SRAM (16.0x the required 32 KB) and 240 MHz cloc…
ESP32-S3 Fall Detection with Edge Impulse
Espressif's ESP32-S3 excels at fall detection via Edge Impulse. The 2-core xtensa-lx7 at 240 MHz with 512 KB SRAM handles 20 KB quantized mo…
ESP32-S3 Fall Detection with TFLite Micro
For fall detection, the ESP32-S3 with TFLite Micro scores Excellent. Its 512 KB internal SRAM (8.0x the required 64 KB) and 240 MHz clock en…
ESP32-S3 Gesture Recognition with Edge Impulse
Edge Impulse enables gesture recognition on the ESP32-S3 by training a classifier on IMU accelerometer and gyroscope data. Connect a 6-axis …
ESP32-S3 Gesture Recognition with TFLite Micro
Espressif's ESP32-S3 excels at gesture recognition via TFLite Micro. The 2-core xtensa-lx7 at 240 MHz with 512 KB SRAM handles 20 KB quantiz…
ESP32-S3 Image Classification with Edge Impulse
The ESP32-S3 is an excellent match for image classification with Edge Impulse. 512 KB SRAM delivers 4.0x the 128 KB minimum while 240 MHz pr…
ESP32-S3 Image Classification with TFLite Micro
The ESP32-S3 is an excellent match for image classification with TFLite Micro. 512 KB SRAM delivers 4.0x the 128 KB minimum while 240 MHz pr…
ESP32-S3 Object Detection with Edge Impulse
Edge Impulse provides an end-to-end pipeline for deploying object detection on the ESP32-S3. You collect images, train a FOMO or MobileNet-S…
ESP32-S3 Object Detection with TFLite Micro
The ESP32-S3 runs quantized object detection models via TFLite Micro at 2-5 FPS. Its 512 KB SRAM and vector instructions handle int8 MobileN…
ESP32-S3 People Counting with Edge Impulse
Espressif's ESP32-S3 excels at people counting via Edge Impulse. The 2-core xtensa-lx7 at 240 MHz with 512 KB SRAM handles 200 KB quantized …
ESP32-S3 People Counting with TFLite Micro
For people counting, the ESP32-S3 with TFLite Micro scores Excellent. Its 512 KB internal SRAM (2.7x the required 192 KB) and 240 MHz clock …
ESP32-S3 Predictive Maintenance with Edge Impulse
The ESP32-S3 is an excellent match for predictive maintenance with Edge Impulse. 512 KB SRAM delivers 8.0x the 64 KB minimum while 240 MHz p…
ESP32-S3 Predictive Maintenance with TFLite Micro
The ESP32-S3 is an excellent match for predictive maintenance with TFLite Micro. 512 KB SRAM delivers 8.0x the 64 KB minimum while 240 MHz p…
ESP32-S3 Sound Classification with Edge Impulse
The ESP32-S3 is an excellent match for sound classification with Edge Impulse. 512 KB SRAM delivers 8.0x the 64 KB minimum while 240 MHz pro…
ESP32-S3 Sound Classification with TFLite Micro
For sound classification, the ESP32-S3 with TFLite Micro scores Excellent. Its 512 KB internal SRAM (8.0x the required 64 KB) and 240 MHz cl…
ESP32-S3 Voice Recognition with Edge Impulse
For voice recognition, the ESP32-S3 with Edge Impulse scores Excellent. Its 512 KB internal SRAM (4.0x the required 128 KB) and 240 MHz cloc…
ESP32-S3 Voice Recognition with TFLite Micro
The ESP32-S3 handles on-device keyword spotting with TFLite Micro using DS-CNN models that classify 1-second audio windows into predefined c…
ESP32-S3 Wildlife Monitoring with Edge Impulse
For wildlife monitoring, the ESP32-S3 with Edge Impulse scores Excellent. Its 512 KB internal SRAM (4.0x the required 128 KB) and 240 MHz cl…
ESP32-S3 Wildlife Monitoring with TFLite Micro
The ESP32-S3 is an excellent match for wildlife monitoring with TFLite Micro. 512 KB SRAM delivers 4.0x the 128 KB minimum while 240 MHz pro…
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Orchestrate ESP32-S3 Edge AI with ForestHub
The ESP32-S3 runs inference on-device. ForestHub on your Linux edge gateway ingests its results over MQTT, orchestrates the sense-reason-act loop as a deterministic, auditable graph, and acts on the line.
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