Espressif
ESP32-C3 Edge AI Guides
400 KB SRAM at 160 MHz supports basic ML inference (anomaly detection, keyword spotting). Single-core limits real-time processing for demanding workloads.
Hardware Specs
| Processor | Single-core RISC-V @ 160 MHz |
| Cores | 1 |
| Clock | 160 MHz |
| SRAM | 400 KB |
| Flash | 4 MB |
| FPU | none |
| Connectivity | Wi-Fi 802.11 b/g/n, Bluetooth 5.0 LE |
| Key Features | RISC-V architecture, Ultra-low cost, Hardware crypto acceleration |
| Price | $1–$3 (chip), $4–$10 (dev board) |
Dev Boards in This Family
16 edge-AI-capable ESP32-C3 development boards with specs and compatibility details.
WeAct Studio ESP32C3CoreBoard
WeAct Studio
400 KB RAM · 160 MHz
Adafruit QT Py ESP32-C3
Adafruit
320 KB RAM · 160 MHz
AirM2M CORE ESP32C3
AirM2M
320 KB RAM · 160 MHz
Smart Bee Motion Mini
Smart Bee
320 KB RAM · 160 MHz
Deneyap Kart G
T3 Foundation
320 KB RAM · 160 MHz
DFRobot Beetle ESP32-C3
DFRobot
320 KB RAM · 160 MHz
Espressif ESP32-C3-DevKitC-02
Espressif
320 KB RAM · 160 MHz
Espressif ESP32-C3-DevKitM-1
Espressif
320 KB RAM · 160 MHz
Ai-Thinker ESP-C3-M1-I-Kit
Ai-Thinker
320 KB RAM · 160 MHz
WEMOS LOLIN C3 Mini
WEMOS
320 KB RAM · 160 MHz
RYMCU ESP32-C3-DevKitM-1
RYMCU
320 KB RAM · 160 MHz
Seeed Studio XIAO ESP32C3
Seeed Studio
320 KB RAM · 160 MHz
Hardware Guides
ESP32-C3 Anomaly Detection with Edge Impulse
For anomaly detection, the ESP32-C3 with Edge Impulse scores Excellent. Its 400 KB internal SRAM (12.5x the required 32 KB) and 160 MHz cloc…
ESP32-C3 Anomaly Detection with TFLite Micro
The ESP32-C3 is a cost-effective option for Wi-Fi-connected anomaly detection. Its 400 KB SRAM runs autoencoder models comfortably while the…
ESP32-C3 Fall Detection with Edge Impulse
The ESP32-C3 is an excellent match for fall detection with Edge Impulse. 400 KB SRAM delivers 6.3x the 64 KB minimum while 160 MHz processes…
ESP32-C3 Fall Detection with TFLite Micro
For fall detection, the ESP32-C3 with TFLite Micro scores Excellent. Its 400 KB internal SRAM (6.3x the required 64 KB) and 160 MHz clock en…
ESP32-C3 Gesture Recognition with Edge Impulse
The ESP32-C3 runs gesture recognition models from Edge Impulse with low inference latency. Its 400 KB SRAM handles IMU classifiers with 5-10…
ESP32-C3 Gesture Recognition with TFLite Micro
The ESP32-C3 is an excellent match for gesture recognition with TFLite Micro. 400 KB SRAM delivers 6.3x the 64 KB minimum while 160 MHz proc…
ESP32-C3 Image Classification with Edge Impulse
Espressif's ESP32-C3 is a solid choice for image classification using Edge Impulse. The risc-v core at 160 MHz with 400 KB SRAM accommodates…
ESP32-C3 Image Classification with TFLite Micro
The ESP32-C3 handles image classification effectively with TFLite Micro. 400 KB SRAM at 160 MHz provides 3.1x headroom over the 128 KB requi…
ESP32-C3 People Counting with Edge Impulse
Espressif's ESP32-C3 is a solid choice for people counting using Edge Impulse. The risc-v core at 160 MHz with 400 KB SRAM accommodates 200 …
ESP32-C3 People Counting with TFLite Micro
The ESP32-C3 handles people counting effectively with TFLite Micro. 400 KB SRAM at 160 MHz provides 2.1x headroom over the 192 KB requiremen…
ESP32-C3 Predictive Maintenance with Edge Impulse
The ESP32-C3 is an excellent match for predictive maintenance with Edge Impulse. 400 KB SRAM delivers 6.3x the 64 KB minimum while 160 MHz p…
ESP32-C3 Predictive Maintenance with TFLite
The ESP32-C3 handles predictive maintenance classification with TFLite Micro, though its single RISC-V core at 160 MHz requires careful reso…
ESP32-C3 Sound Classification with Edge Impulse
Espressif's ESP32-C3 excels at sound classification via Edge Impulse. The 1-core risc-v at 160 MHz with 400 KB SRAM handles 40 KB quantized …
ESP32-C3 Sound Classification with TFLite Micro
Espressif's ESP32-C3 excels at sound classification via TFLite Micro. The 1-core risc-v at 160 MHz with 400 KB SRAM handles 40 KB quantized …
ESP32-C3 Voice Recognition with Edge Impulse
The ESP32-C3 handles voice recognition effectively with Edge Impulse. 400 KB SRAM at 160 MHz provides 3.1x headroom over the 128 KB requirem…
ESP32-C3 Wildlife Monitoring with Edge Impulse
The ESP32-C3 handles wildlife monitoring effectively with Edge Impulse. 400 KB SRAM at 160 MHz provides 3.1x headroom over the 128 KB requir…
ESP32-C3 Wildlife Monitoring with TFLite Micro
Espressif's ESP32-C3 is a solid choice for wildlife monitoring using TFLite Micro. The risc-v core at 160 MHz with 400 KB SRAM accommodates …
Related Guides
Best Microcontroller for Machine Learning
Compare ESP32-S3, STM32H7, ESP32-C3, and Arduino Nano 33 BLE for on-device ML. Specs, benchmarks, and use-case recommendations.
ESP32 vs STM32 for AI Applications
Compare ESP32 and STM32 for edge AI. Architecture, ML performance, tooling, connectivity, and cost analysis for embedded ML projects.
Fall Detection in the Smart Home with a Local Edge Agent
How an Edge Agent could detect a fall locally on the device and alert a stored contact, without any video or audio leaving the home.
How to Run TensorFlow Lite on ESP32
Step-by-step guide to running TFLite Micro (LiteRT) on ESP32 with ESP-IDF. Tensor arena, operator registration, and C inference code included.
HVAC Edge Agent, On-Device AI for Building Control
An HVAC Edge Agent fuses CO2, temperature and occupancy on-device, writing only setpoints to the controller, never in the loop. GDPR-friendly edge AI.
On-Device Knowledge Retention with Edge Agents
How an on-device Edge Agent captures implicit service knowledge, makes it searchable, and guards against the skills shortage, fully offline at the machine.
Predictive Maintenance Across a Distributed Fleet
Local anomaly detection plus federated learning. Edge Agents explain faults on site and the fleet learns together, without centralizing raw data.
Predictive Maintenance with Edge AI
Deploy edge AI for predictive maintenance. Vibration analysis, anomaly detection, and ROI calculation for MCU-based monitoring on factory equipment.
Small Language Models (SLM) on Edge Hardware
Why an on-device small language model handles most industrial tasks, and how the intelligence cascade from rules to cloud keeps data on-premises.
Smart Home Setup with a Local Edge Agent Assistant
An Edge Agent turns smart home setup into a guided local dialog. On-device AI, private, no mandatory account, with MQTT device discovery.
The Virtual Service Technician as an Edge Agent
An on-device Edge Agent acts as a virtual service technician that detects machine faults and guides operators step by step, with no ticket needed.
Why AI Agents Run on the Machine, Not the Cloud
Four reasons for on-device AI over the cloud. Latency, cost, connectivity and data sovereignty. How an Edge Agent works right on the device.
Other Microcontrollers
EFR32MG
Silicon Labs
256 KB RAM · 40 MHz
ESP32
Espressif
520 KB RAM · 240 MHz
ESP32-C6
Espressif
512 KB RAM · 160 MHz
ESP32-S2
Espressif
320 KB RAM · 240 MHz
ESP32-S3
Espressif
512 KB RAM · 240 MHz
GAP8
GreenWaves Technologies
512 KB RAM · 250 MHz
i.MX RT1052
NXP
512 KB RAM · 600 MHz
i.MX RT1062
NXP
1024 KB RAM · 600 MHz
i.MX RT1064
NXP
1024 KB RAM · 600 MHz
LPC55xx
NXP
320 KB RAM · 150 MHz
nRF52832
Nordic Semiconductor
64 KB RAM · 64 MHz
nRF52833
Nordic Semiconductor
128 KB RAM · 64 MHz
nRF52840
Nordic Semiconductor
256 KB RAM · 64 MHz
RA6M5
Renesas
512 KB RAM · 200 MHz
SAMD51
Microchip
256 KB RAM · 120 MHz
SAME51
Microchip
256 KB RAM · 120 MHz
STM32F3
STMicroelectronics
80 KB RAM · 72 MHz
STM32F4
STMicroelectronics
192 KB RAM · 168 MHz
STM32F7
STMicroelectronics
512 KB RAM · 216 MHz
STM32G4
STMicroelectronics
128 KB RAM · 170 MHz
STM32H5
STMicroelectronics
640 KB RAM · 250 MHz
STM32H7
STMicroelectronics
1024 KB RAM · 480 MHz
STM32L4
STMicroelectronics
128 KB RAM · 80 MHz
STM32L5
STMicroelectronics
256 KB RAM · 110 MHz
STM32U5
STMicroelectronics
786 KB RAM · 160 MHz
STM32WB
STMicroelectronics
256 KB RAM · 64 MHz
Orchestrate ESP32-C3 Edge AI with ForestHub
The ESP32-C3 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.
Get Started Free