Texas Instruments

MSPM0G5187 - 80MHz Cortex-M0+ MCU, 128KB Flash, NPU | TI

N.º de pieza: MSPM0G5187 ✓ Activo
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1.62 V to 3.6 V Vdss 64-LQFP (10x10 mm) Package 80 MHz Speed 128 KB (128K x 8) Memory
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Precio actualizado: 2026-08-30
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MSPM0G5187 Descripción general

The Texas Instruments MSPM0G5187 is a 32-bit ultra-low-power microcontroller based on an enhanced Arm Cortex-M0+ core operating at up to 80MHz, integrating 128KB of flash memory, 32KB of SRAM, USB 2.0 Full-Speed, I2S, a 12-bit ADC, and the TinyEngine NPU for edge-AI acceleration, housed in a 64-pin LQFP (10x10 mm) package.

A microcontroller (MCU) is a single-chip embedded processor that combines a CPU core, memory, and programmable peripherals to govern a dedicated function within a larger system. MCUs sit within the broader hierarchy of semiconductor devices under the microcontroller and embedded processor category, and the MSPM0G5187 belongs to the MSPM0G series within Texas Instruments' long-standing MSP ultra-low-power MCU family, positioned for energy-efficient embedded sensing and on-device machine learning designs.

Key differentiating features include the integrated TinyEngine NPU, which delivers up to 90x lower inference latency and more than 120x lower energy per inference compared with MCUs executing neural networks purely on the CPU, enabling always-on edge AI at milliwatt power budgets. The 128KB flash and 32KB SRAM support compact sensor-fusion models, while USB 2.0 FS, I2S, UART, SPI, and I2C interfaces cover connectivity and digital audio needs.

Architecturally, the device uses a 32-bit Arm Cortex-M0+ core with a memory protection unit (MPU) and nested vectored interrupt controller (NVIC) for deterministic real-time behavior. The TinyEngine NPU offloads convolutional neural network inference from the CPU, reducing both latency and energy per inference. Cybersecurity enablers and high-performance integrated analog round out the mixed-signal capability. The supply voltage range is 1.62V to 3.6V with a -40C to +125C operating temperature range per TI product documentation.

Typical applications include industrial automation and predictive maintenance, smart sensors with anomaly detection, portable medical monitoring devices, and battery-powered edge-AI endpoints where USB host connectivity or I2S digital audio is required alongside low-power inference.

When designing, decouple all supply pins with 100nF ceramic capacitors placed close to the device, and budget SRAM carefully for NPU model weights and activations; multiple low-power modes extend battery life.

This page synthesizes distributor availability data, drop-in alternative analysis, and practical design notes not found in the manufacturer datasheet.

Alternativas directas para MSPM0G5187 — mismo encapsulado, compatible pin a pin. Se excluyen las piezas de otro encapsulado que requieren retrabajo de la PCB.

Variantes de esta serie

Modelos de la misma serie compatibles directamente con MSPM0G5187 (mismo factor de forma y huella) — difiere en Core Processor, Peripherals.

Texas Instruments
Core Processor: Arm Cortex-M0+
Peripherals: CAN-FD, MATHACL, OPA, COMP, DAC, ADC
Comparar con MSPM0G5187 →

Herramienta de comparación rápida — seleccione piezas alternativas para compararlas lado a lado:

MSPM0G5187SPMR

✅ Sustitución directa
📦 64-LQFP (10x10 mm)
orderable packaging variant of the same silicon, identical 128KB flash / 80MHz / NPU

📋 Alternativa de referencia (no en el catálogo)

MSPM0G5186

✅ Sustitución directa ⚠️ Especificaciones sin verificar
📦 64-LQFP (10x10 mm)
same G518x family, reduced feature/NPU configuration vs G5187; verify exact peripheral deltas in TI datasheet

📋 Alternativa de referencia (no en el catálogo)

MSPM0G5185

✅ Sustitución directa ⚠️ Especificaciones sin verificar
📦 64-LQFP (10x10 mm)
same G518x family, entry configuration of the family; pin-to-pin within family per TI pinout tables

📋 Alternativa de referencia (no en el catálogo)

MSPM0G3507

✅ Sustitución directa ⚠️ Especificaciones sin verificar
Texas Instruments
📦 64-LQFP (10x10 mm)
Arm Cortex-M0+ · 32-bit · 80 MHz · 128 KB (128K x 8) · 32 KB · 12-bit · 2 x ADC, 4 Msps · 1 x 12-bit

✓ En stock

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MSPM0G5187 Valores máximos y características eléctricas

Core Processor Arm Cortex-M0+ (32-bit)
Core Frequency 80 MHz
Flash Memory 128 KB (128K x 8)
SRAM 32 KB
Hardware Accelerator TinyEngine NPU (edge AI)
USB Interface USB 2.0 Full-Speed
Audio Interface I2S
ADC Resolution 12-bit
Supply Voltage Range 1.62 V to 3.6 V
Temperatura de funcionamiento -40C to +125C
Encapsulado 64-LQFP (10x10 mm)
Tipo de montaje Surface Mount
Ancho del bus de datos 32-bit
Series MSPM0G
Evaluation Kit LP-MSPM0G5187 LaunchPad
Peripherals UART, SPI, I2C, timers, DMA, cybersecurity enablers

Guía de configuración de pines de MSPM0G5187 64-lqfp (10x10 mm)

Configuración de pines para MSPM0G5187 (encapsulado 64-lqfp (10x10 mm)). Este CI digital incluye GPIO, interfaces de comunicación (UART, SPI, I2C) y pines de alimentación. Consulte la hoja de datos del fabricante para conocer las funciones alternativas de los pines y las opciones de configuración. Esencial para el diseño de sistemas embebidos y el diseño de PCB.

Diagrama de patillaje del encapsulado 64-lqfp (10x10 mm) para MSPM0G5187

No hay datos detallados de patillaje disponibles para MSPM0G5187.

Consulte la hoja de datos para ver la configuración completa de patillas.

Aplicaciones típicas

MSPM0G5187 es adecuado para 6 aplicacións: Industrial Predictive Maintenance, Smart Sensors with Anomaly Detection, Portable Medical Monitoring, Edge AI Voice and Audio Devices, Building Automation and HVAC Control, USB-Connected Data Loggers.

🏭

Industrial Predictive Maintenance

The MSPM0G5187 fits predictive-maintenance endpoints because its TinyEngine NPU classifies vibration and current signatures on-device with up to 90x lower latency than CPU inference, enabling immediate shutdown decisions without cloud round-trips. The 12-bit ADC samples motor current and accelerometer channels, while UART/SPI/I2C link to industrial sensor front-ends. In a typical deployment the MCU continuously streams ADC data to the NPU, which runs an anomaly-detection model within the 32KB SRAM budget, consuming far less energy than duty-cycled wireless inference. The -40C to +125C range covers cabinet and drive-mounted installations, and cybersecurity enablers protect model and firmware integrity on the factory floor.

🧩

Smart Sensors with Anomaly Detection

Smart sensors benefit from the MSPM0G5187's combination of ultra-low-power Cortex-M0+ operation (1.62V to 3.6V supply) and on-chip NPU inference at more than 120x lower energy per inference, extending battery life in always-on monitoring nodes. The 12-bit ADC digitizes gas, humidity, or acoustic sensor outputs, and the NPU filters false positives locally so the radio transmits only actionable events. USB 2.0 Full-Speed simplifies bench configuration and data offload during commissioning, while I2C and SPI connect digital sensors directly. Multiple low-power modes between inference bursts allow multi-year battery operation, and the 64-LQFP 10x10 mm footprint suits compact sensor housings.

💊

Portable Medical Monitoring

For portable medical devices such as vital-sign patch monitors, the MSPM0G5187 offers battery-friendly operation from a 1.62V to 3.6V rail, low-power sleep modes, and NPU-accelerated arrhythmia or activity classification that would otherwise drain batteries if executed on the CPU or in the cloud. The 12-bit ADC with integrated analog front-end capability conditions biopotential and optical sensor signals, and I2S can interface digital audio or dedicated AFE devices. USB 2.0 FS provides clinician data offload without extra bridge ICs. Operating to +125C supports autoclave-adjacent storage conditions, and cybersecurity enablers assist with patient-data protection requirements at the edge.

🎧

Edge AI Voice and Audio Devices

The MSPM0G5187 suits keyword-spotting and acoustic-event devices because the I2S interface connects digital microphones and audio codecs directly, and the TinyEngine NPU executes small CNNs with up to 90x lower latency than CPU inference - fast enough for real-time wake-word response. With 128KB flash and 32KB SRAM, compact speech-command models fit on-chip without external memory, keeping the bill of materials minimal. The USB 2.0 Full-Speed port can present the device as an audio or HID class peripheral to a host PC. Because inference runs at microwatt-to-milliwatt energy levels, the design achieves always-on listening in battery-powered form factors.

🏢

Building Automation and HVAC Control

In building automation nodes, the MSPM0G5187 handles sensing, local decision-making, and connectivity in one chip. The Cortex-M0+ at 80MHz executes control loops with deterministic NVIC interrupt latency, the 12-bit ADC reads temperature, pressure, and current sensors, and UART/I2C buses communicate with network coprocessors and digital sensors. The NPU enables occupancy or air-quality pattern classification at the node, reducing uplink traffic to the BMS controller. A 1.62V to 3.6V supply suits battery- or bus-powered thermostats and damper actuators, while the -40C to +125C temperature range and 64-LQFP 10x10 mm package support both panel-mounted and rooftop equipment enclosures with minimal PCB area.

🖥️

USB-Connected Data Loggers

The MSPM0G5187 is a strong fit for USB data loggers because its USB 2.0 Full-Speed controller enumerates directly as a device with no external USB PHY or bridge chip, cutting cost and board area versus non-USB MCUs that need a separate UART-USB converter. The 128KB flash stores configuration and logged datasets or buffers to the 32KB SRAM between host reads, while the 12-bit ADC and GPIO capture sensor channels. The NPU can pre-filter data on-device, so only anomalous events are written, extending storage capacity. Low-power modes keep multi-month battery-backed logging feasible, and the 10x10 mm LQFP fits slim enclosure profiles.

Resumen de productos recomendados

ADS1115 Precision external ADC option Se usa en: Industrial Predictive Maintenance TMP1075 Digital temperature sensor for motor monitoring Se usa en: Industrial Predictive Maintenance, Building Automation and HVAC Control HDC3020 Low-power humidity sensor Se usa en: Smart Sensors with Anomaly Detection TMP117 Texas Instruments Se usa en: Smart Sensors with Anomaly Detection, USB-Connected Data Loggers AFE4400 Integrated analog front-end for pulse oximetry Se usa en: Portable Medical Monitoring ADS1292R Two-channel biopotential AFE for ECG Se usa en: Portable Medical Monitoring TLV320AIC3110 Low-power audio codec with I2S interface Se usa en: Edge AI Voice and Audio Devices SPH0641LU4H I2S digital microphone Se usa en: Edge AI Voice and Audio Devices TPS22860 Load switch for sensor power gating Se usa en: Building Automation and HVAC Control BQ25180 Li-Ion charger for USB-powered logger Se usa en: USB-Connected Data Loggers
What is the MSPM0G5187 microcontroller?
The MSPM0G5187 is a 32-bit ultra-low-power microcontroller from Texas Instruments based on an enhanced Arm Cortex-M0+ core running at up to 80MHz. It integrates 128KB of flash, 32KB of SRAM, USB 2.0 Full-Speed, I2S, a 12-bit ADC, and the TinyEngine NPU hardware accelerator for edge AI, and it is packaged in a 64-pin LQFP (10x10 mm). According to the TI datasheet, it belongs to the MSPM0G mixed-signal MCU series within the MSP ultra-low-power family.
What are the key specifications of MSPM0G5187 that engineers should know?
The MSPM0G5187 combines an 80MHz Arm Cortex-M0+ core, 128KB flash, 32KB SRAM, USB 2.0 FS, I2S, a 12-bit ADC, and the TinyEngine NPU in a 64-LQFP (10x10 mm) package. It operates from 1.62V to 3.6V and across -40C to +125C. The NPU achieves up to 90x lower latency and over 120x lower energy per inference than CPU-only execution, per TI documentation, making it a leading choice for low-power edge-AI MCU designs.
What is the TinyEngine NPU in the MSPM0G5187 and why does it matter?
The TinyEngine NPU is a dedicated neural-network hardware accelerator integrated on the MSPM0G5187 that offloads deep-learning inference from the Cortex-M0+ CPU. According to TI, it delivers up to 90x lower latency and more than 120x lower energy per inference versus MCUs without a hardware accelerator. This enables always-on anomaly detection, keyword spotting, and sensor-fusion classification at milliwatt-level power budgets in battery-powered devices.
What is the price of MSPM0G5187SPMR?
Pricing for the MSPM0G5187SPMR (64-LQFP, Tape & Reel) is quoted through distributors such as DigiKey and Mouser and varies by order quantity; XAIPART lists quantity-break pricing from 1 to 1000 units with a request-quote model as of 2026-08-30. Because this is a newly released device (DigiKey product page 28721540), stock is currently 'ships today' at distributors. Contact XAIPART sales for a current, quantity-specific quote.
Where can I buy MSPM0G5187 online?
The MSPM0G5187 (orderable MPN MSPM0G5187SPMR in 64-LQFP) is available from authorized distributors including DigiKey (product 28721540, ships today as of 2026-08-30) and Mouser, as well as directly through TI.com. XAIPART also supplies this part with quantity-break pricing and technical support. For production volumes, request a quote through XAIPART to compare lead times and pricing across stocking distributors.
What is the lead time and stock status for MSPM0G5187?
As of 2026-08-30, DigiKey lists the MSPM0G5187SPMR as in stock with same-day shipping ('Buy now, ships today'), indicating healthy initial availability for this newly released device. Because the part is new to market, standard lead times for direct factory orders from TI typically apply for large volumes. XAIPART recommends placing production orders 12-16 weeks ahead while the supply chain ramps, and cross-checking stock on DigiKey and Mouser product pages.
What is the difference between MSPM0G5187 and MSPM0G3507?
The MSPM0G5187 adds the TinyEngine NPU for edge-AI inference and USB 2.0 Full-Speed, while the MSPM0G3507 is a lower-cost MSPM0G-series MCU without the NPU, targeting general-purpose mixed-signal control. Both use Arm Cortex-M0+ cores and share the MSPM0 peripheral architecture and LQFP package options, so the G3507 suits cost-sensitive control tasks, whereas the G5187 is the correct choice when on-device neural-network inference with 120x lower inference energy is required.
MSPM0G5187 vs STM32 - which is better for edge AI applications?
For edge-AI workloads at ultra-low power, the MSPM0G5187 has a clear advantage: its integrated TinyEngine NPU delivers up to 90x lower latency and over 120x lower energy per inference than CPU-only execution, which most general-purpose MCUs (including typical Cortex-M0+ STM32 parts) must perform in software. If your application is conventional control or connectivity without machine learning, mainstream Cortex-M MCUs remain cost-competitive. Choose the MSPM0G5187 specifically when always-on, battery-powered inference is a core requirement.
When should I choose MSPM0G5187 over MSPM0G3507?
Choose the MSPM0G5187 when your design requires on-device machine learning (keyword spotting, anomaly detection, predictive maintenance classification), USB 2.0 Full-Speed host/device connectivity, or I2S digital audio - the G5187 uniquely combines the TinyEngine NPU with these interfaces in the MSPM0G family. Choose the MSPM0G3507 when none of those are needed and unit cost is the dominant factor, since it omits the NPU and USB while retaining the same Cortex-M0+ platform, 12-bit ADC, and MSPM0 software ecosystem.
What is the best drop-in replacement for MSPM0G5187?
The closest same-brand drop-in options are other MSPM0G518x family variants sharing the 64-LQFP footprint, such as MSPM0G5185 and MSPM0G5186, which differ mainly in feature/NPU configuration and are pin-to-pin compatible within the family (verify against the TI datasheet pinout tables). The MSPM0G3507 in 64-LQFP offers the same MSPM0 platform but is not a guaranteed pin-for-pin match. No cross-brand pin-compatible equivalent for the G5187 with NPU is currently listed in vendor cross-reference tools as of 2026-08-30.
Where can I download the MSPM0G5187 datasheet PDF?
The official MSPM0G5187 datasheet PDF is available free from Texas Instruments at https://www.ti.com/lit/ds/symlink/mspm0g5187.pdf, covering the mixed-signal microcontrollers with TinyEngine NPU (approximately 118 pages per aggregator listings). The TI product page at https://www.ti.com/product/MSPM0G5187 also provides the Technical Reference Manual, user guides, and application notes. XAIPART links directly to the manufacturer datasheet - always prefer the TI-hosted PDF for the latest revision.
Where can I find the MSPM0G5187 pinout for the 64-LQFP package?
The complete MSPM0G5187 64-LQFP (10x10 mm) pinout, including power, GPIO, and peripheral multiplexing assignments, is documented in the TI datasheet at https://www.ti.com/lit/ds/symlink/mspm0g5187.pdf in the Pin Attributes section. Because MSPM0G devices multiplex many functions per pin, consult the pin-mux tables alongside the SysConfig tool in TI's MSPM0 SDK, which generates verified pin-configuration code. XAIPART does not republish the full 64-pin table; use the manufacturer source to avoid mux errors.
Is the MSPM0G5187 suitable for portable medical and wearable devices?
Yes. The MSPM0G5187 operates from 1.62V to 3.6V, offers multiple low-power modes for battery operation, and its TinyEngine NPU performs inference with more than 120x lower energy per inference than CPU execution - ideal for always-on vital-sign anomaly detection in portable medical devices. The 12-bit ADC supports sensor interfaces, USB 2.0 FS provides data offload, and the -40C to +125C range plus integrated cybersecurity enablers support regulated product requirements. Note: medical certification of the end system remains the designer's responsibility.
Is the MSPM0G5187 RoHS compliant and lead-free?
Texas Instruments lists standard MSPM0G-series devices as RoHS-compliant and lead-free on its product pages; however, XAIPART's verified data for this listing does not include the explicit compliance certificate for the MSPM0G5187 package variant, so confirm the exact Green/RoHS designation on the TI product page (https://www.ti.com/product/MSPM0G5187) or its material declaration report before final BOM approval. TI generally provides REACH and halogen-free data in its online compliance documentation for active catalog parts.
Does the MSPM0G5187 support my development tools and what kit should I use?
Yes - the MSPM0G5187 is supported by the LP-MSPM0G5187 LaunchPad development kit (with XDS110-ET debug interface over SWD), the MSPM0G SDK, TI SysConfig, Code Composer Studio, and Arm Keil MDK (CMSIS pack MSPM0G511X_G518X_DFP, per keil.arm.com). The Arm Cortex-M0+ core also works with GCC/IAR toolchains. The TinyEngine NPU is programmed through TI's edge-AI tool flow, which converts trained models for on-device inference within the 128KB flash and 32KB SRAM budget.
Is MSPM0G5187 the same as MSPM0G5187SPMR?
Not exactly - MSPM0G5187 is the base device (catalog) part number, while MSPM0G5187SPMR is the orderable MPN specifying the 64-LQFP (10x10 mm), Tape & Reel packaging option. Functionally the silicon is identical; the suffix letters encode package, reel quantity, and temperature/grade options. When ordering, always use the full orderable MPN (such as MSPM0G5187SPMR, DigiKey product 28721540) to receive the correct 64-pin LQFP package on a reel.

Datos de referencia de ingeniería para MSPM0G5187 — comparación, orientación de diseño e información de cumplimiento.

Guía de selección

Choose the MSPM0G5187 when your design needs on-device machine learning at ultra-low power: its TinyEngine NPU delivers up to 90x lower latency and over 120x lower energy per inference than CPU-only MCUs, and it uniquely pairs that with USB 2.0 Full-Speed and I2S in the MSPM0G family. Choose MSPM0G5186 or MSPM0G5185 if you want the same 64-LQFP platform with a reduced feature set at lower cost and your application does not need the full peripheral/NPU configuration. Choose MSPM0G3507 when cost dominates and neither the NPU nor USB is required, accepting a firmware/porting effort despite the shared MSPM0 ecosystem. For ordering, MSPM0G5187SPMR is the Tape & Reel form of identical silicon. All listed options share the 64-LQFP (10x10 mm) footprint family, but verify pin-mux compatibility in the TI datasheet before any drop-in swap. Avoid this part if your model exceeds the 128KB flash / 32KB SRAM budget - step up to a larger-class MCU instead.

Comparación con alternativas

Parámetro Este producto MSPM0G5187SPMR MSPM0G5186 MSPM0G5185 MSPM0G3507
Package 64-LQFP (10x10 mm) 64-LQFP (10x10 mm) - same 64-LQFP (10x10 mm) - same 64-LQFP (10x10 mm) - same 64-LQFP (10x10 mm) - same
Brand Texas Instruments Texas Instruments Texas Instruments Texas Instruments Texas Instruments
ADC 12-bit 12-bit 12-bit (family standard) 12-bit (family standard) 12-bit

Diferenciadores clave

  • Integrated TinyEngine NPU for edge AI (frente a MSPM0G3507)
  • Native USB 2.0 Full-Speed (frente a MSPM0G3507)
  • Same MSPM0 ecosystem across family (frente a MSPM0G5186)
  • Trade-off: 128KB/32KB memory ceiling (frente a MSPM0G5187SPMR)

Notas de diseño

Decouple every VDD/VDDA pin with 100nF ceramic capacitors placed within 2 mm of the pin, plus one bulk 4.7uF-10uF capacitor near the device. On the 64-LQFP 10x10 mm footprint, use the exposed fanout layer to tie the thermal pad or ground plane with an array of vias. Keep the USB FS D+/D- traces as a 90-ohm differential pair with length matching, and route the I2S clock lines away from the ADC input traces to preserve 12-bit ADC noise performance.

The 1.62V to 3.6V supply range allows direct Li-Ion cell operation, but remember that flash programming and NPU-intensive inference bursts raise peak current versus idle mode - verify your regulator can supply the peak from the datasheet electrical characteristics tables. For battery designs, exploit the MSPM0 low-power modes: park the CPU in standby between NPU inference frames and gate sensor supplies with a load switch (e.g., TPS22860) to minimize quiescent drain.

Budget SRAM before choosing the NPU model: 32KB total must hold model weights, activations, and the application stack, so quantize models to int8 and validate with TI's edge-AI toolchain early in the project. Also remember MSPM0G pins are heavily multiplexed - generate the pin configuration with TI SysConfig rather than hand-editing registers, and confirm your final pin-mux against the 64-LQFP pinout table in the datasheet to avoid footprint rework.

Estimated: even at a conservative 20 mA average at 3.3V (66 mW), the 64-LQFP theta_JA of roughly 60-70 C/W on a standard 4-layer board yields under 5C junction rise - thermal design is rarely limiting for this MCU. Concentrate instead on ADC noise and layout quality; only high-drive GPIO or USB bus-powered scenarios with many active peripherals warrant a copper-pour review.

Información de cumplimiento

RoHS
Unknown
REACH
Unknown
AEC-Q100
Not Applicable
Libre de plomo
Unknown
Libre de halógenos
Unknown
Minerales en conflicto
Unknown

Compliance data not present in verified web data for this listing. TI product pages typically list RoHS/Green status per package option - confirm at https://www.ti.com/product/MSPM0G5187 before BOM approval.

Datos verificados el: 2026-08-30 — datos verificados y seleccionados por el equipo de ingeniería de componentes de XAIPART

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Componentes & términos relacionados

Texas Instruments MSPM0G5187 MSPM0G5187SPMR MSPM0G3507 MSPM0G5186 MSPM0G5185 Arm Cortex-M0+ microcontroller MCU TinyEngine NPU edge AI USB 2.0 Full-Speed I2S 12-bit ADC 64-LQFP QFN/QFP family surface mount LP-MSPM0G5187 LaunchPad MSPM0G series MSP ultra-low-power MCU family RoHS predictive maintenance anomaly detection portable medical devices
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