Hardware Comparison
STM32H7 vs i.MX RT1062 for Image Classification
Winner: STM32H7 (score 100 vs 85)
Published 2026-04-02
Specs Comparison
| Spec | STM32H7 | i.MX RT1062 |
|---|---|---|
| Manufacturer | STMicroelectronics | NXP |
| Architecture | ARM Cortex-M7 @ 480 MHz | ARM Cortex-M7 @ 600 MHz |
| SRAM | 1024 KB | 1024 KB |
| Flash | 2 MB | 8 MB |
| ML Acceleration | DSP, FPU | DSP, FPU |
| Connectivity | Ethernet, USB OTG HS/FS | Ethernet, USB OTG HS/FS |
| Chip Price | $8-20 | $6-12 |
| Image Classification Score |
Detailed Comparison
The STM32H7 edges ahead for image classification with a compatibility score of 100 vs 85 for the i.MX RT1062. However, each platform has distinct advantages depending on deployment requirements. Memory: The STM32H7 provides 1024 KB SRAM, while the i.MX RT1062 offers 1024 KB. For image classification's 128 KB minimum requirement, both provide equivalent capacity. Performance: The STM32H7 runs at 480 MHz (cortex-m7, DSP) vs the i.MX RT1062 at 600 MHz (cortex-m7, DSP). Inference performance is comparable at these clock speeds. Connectivity: STM32H7 offers Ethernet, USB OTG HS/FS. i.MX RT1062 provides Ethernet, USB OTG HS/FS. Cost: STM32H7 chips run $8-20 (dev boards $30-80), while i.MX RT1062 chips cost $6-12 (dev boards $25-40). The i.MX RT1062 wins on cost per unit. Choose the STM32H7 when: the STMicroelectronics ecosystem fits your toolchain, or hardware variety is important (22 PlatformIO boards). Choose the i.MX RT1062 when: fastest possible inference is required, the NXP toolchain is preferred, or you need crossover mcu (600 mhz cortex-m7).
Explore Each Platform
FAQ
- Is STM32H7 or i.MX RT1062 better for image classification?
- STM32H7 scores higher (100 vs 85) for image classification. The STM32H7's 1024 KB SRAM and 480 MHz clock provide a slight edge. However, ecosystem fit and connectivity needs should also influence your decision.
- What's the price difference between STM32H7 and i.MX RT1062?
- STM32H7 chips cost $8-20, dev boards $30-80. i.MX RT1062 runs $6-12 per chip, $25-40 for dev boards. Pricing is comparable at volume.
- Can both STM32H7 and i.MX RT1062 use TensorFlow Lite?
- Yes, the STM32H7 (cortex-m7) supports TFLite Micro. The i.MX RT1062 (cortex-m7) also supports TFLite Micro.
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