MCU Selection Engine — Microcontroller Comparison Tool
Compare microcontrollers side by side using a weighted scoring system based on cost, pin count, and flash memory. Select any combination of AVR, STM32, PIC, MSP430, or RP2350 chips and let the decision engine rank them for your specific project requirements.
Supported Microcontroller Families
The tool covers common MCU families used in embedded systems, Arduino projects, robotics, IoT, and low-power sensor designs:
- AVR 8-bit (Microchip/Atmel): ATtiny13, ATtiny45, ATtiny85, ATmega32, ATmega328P, ATmega32U4, ATmega2560
- ARM 32-bit (STMicroelectronics / Raspberry Pi): STM32F103C8T6, STM32F401RE, STM32L4R5ZIT6, RP2350
- MSP430 16-bit (Texas Instruments): MSP430G2553, MSP430F5529, MSP430FR5994
- PIC (Microchip): PIC12F683, PIC16F877A, PIC18F4550
- SoC / BLE: nRF52840 (Nordic Semiconductor)
MCU Specs at a Glance
| MCU | Family | Flash | Pins | Price (approx.) | Best For |
|---|---|---|---|---|---|
| ATtiny13 | AVR 8-bit | 1 KB | 8 | ~$0.42 | Ultra-minimal single-task designs |
| ATtiny45 | AVR 8-bit | 4 KB | 8 | ~$0.75 | Low-power sensor nodes |
| ATtiny85 | AVR 8-bit | 8 KB | 8 | ~$0.95 | Compact projects, Digispark boards |
| ATmega328P | AVR 8-bit | 32 KB | 28 | ~$2.10 | Arduino Uno, general-purpose projects |
| ATmega2560 | AVR 8-bit | 256 KB | 100 | ~$5.50 | Arduino Mega, high pin-count projects |
| STM32F103C8T6 | ARM Cortex-M3 | 64 KB | 37 | ~$3.50 | Blue Pill, 32-bit performance on a budget |
| STM32F401RE | ARM Cortex-M4 | 512 KB | 51 | ~$5.20 | DSP, floating-point, Nucleo boards |
| RP2350 | ARM Cortex-M33 | 520 KB | 30 | ~$0.80 | Dual-core, RISC-V option, Raspberry Pi ecosystem |
| MSP430G2553 | MSP430 16-bit | 16 KB | 20 | ~$1.50 | Ultra-low-power battery applications |
| PIC16F877A | PIC 8-bit | 14 KB | 40 | ~$3.60 | Classic PIC projects, industrial use |
| nRF52840 | ARM Cortex-M4 | 1 MB | 48 | ~$4.20 | Bluetooth 5.0 BLE, USB, IoT devices |
How the Scoring Works
The engine uses multi-criteria decision analysis (MCDA) to score each chip:
- Min-Max Normalization: Each spec (price, pins, flash) is scaled to a 0–1 range so they can be compared on equal footing regardless of units.
- Bayesian Priority Weighting: You assign a weight (1–10) to each criterion. Higher weight means that spec has more influence on the final score.
- Utility Score: The weighted average of normalized specs — the higher the score, the better the chip fits your stated priorities.
- Wald Minimax Criterion: Identifies the chip with the best worst-case normalized spec. The safest choice when even one weak spec could be a problem.
Keyword Tags
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