Syntiant’s NDP120 is a low-power embedded processor designed to run always-on audio and sensor AI in devices such as voice-enabled products. Its headline “25×” figure is a vendor-stated increase in tensor throughput over Syntiant Core 1, used in the NDP100 and NDP101—not a promise that every application runs 25 times faster or uses 25 times less power.
What the Syntiant NDP120 does
Announced on January 6, 2021, the NDP120 is a special-purpose Neural Decision Processor for audio and sensor inference in power-constrained devices. It is not a general-purpose application processor. Syntiant describes it as capable of handling tasks such as keyword spotting, multiple wake words, local-command recognition, speaker identification, noise suppression, beamforming, echo cancellation, speech enhancement and event detection. These are vendor-described use cases, not independent performance results. Syntiant’s launch announcement
The chip can also combine audio with sensor inputs. Syntiant’s examples include infrared, multi-axis acceleration, tilt, magnetic-field and pressure sensors. That makes the NDP120 relevant to products that need to detect a sound or spoken command alongside other local signals, without sending every inference task to a cloud service.
What the 25× performance claim means
Syntiant’s January 2021 announcement says Core 2 delivers “25x the tensor throughput” of Core 1, the architecture in the NDP100 and NDP101. The figure describes tensor throughput for that specific architecture-to-architecture comparison. It does not establish a 25× improvement in end-to-end latency, model accuracy, battery life or every workload. It is a manufacturer claim; the cited announcement does not provide an independent benchmark substantiating the exact multiplier.
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For a design decision, tensor throughput alone is not enough. Compare processors using the same model and task, and examine accuracy, end-to-end latency, power under the same duty cycle, supported audio streams and concurrent networks, memory, interfaces, package, toolchain and integration cost. The cited sources do not present a controlled head-to-head test against competing processors.
How the NDP120 is built
The NDP120 combines Syntiant Core 2 with an embedded Arm Cortex-M0 and a user-programmable HiFi-3 DSP. Syntiant said Core 2 supports more than 7 million parameters and multiple concurrent heterogeneous networks, allowing more than one network or type of inference workload to run on the chip. The launch announcement also lists support for up to seven audio streams, I2S/TDM audio output, Quad SPI, I2C and up to 26 GPIO pins, along with stand-alone operation and firmware decryption and authentication. These are vendor-published capabilities. Syntiant’s NDP120 announcement
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Syntiant’s portfolio page lists Core 2 memory as 896 kB of program memory and 128 kB of data memory; Cortex-M0 memory as 48 kB; and HiFi-3 memory as 96 kB of instruction memory and 192 kB of data memory. It also lists voltage and clock ranges. Treat these as portfolio specifications and consult the linked product brief or datasheet before designing around them. Syntiant’s Neural Decision Processors portfolio
Power figures depend on the workload
There is no single power figure in the cited announcements that can be applied to every NDP120 design. In March 2021, Syntiant said an NDP120-based Android implementation could activate Google Assistant on “Hey Google” or “Ok Google” at under 280 µW. That is a company-reported figure for the specified wake-word use case, not a guarantee for other models or product configurations. Syntiant’s Google Assistant hotword announcement
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A separate launch-release example quoted BraveHeart Wireless co-founder and VP of hardware engineering Stuart MacEachern saying the NDP120 delivered processing “at under one milliwatt” in their design. This, too, is a company-reported example tied to a particular design. Actual system power depends on the model, audio path, sensors, host, duty cycle and surrounding circuitry.
Packages, production status and buying context
Syntiant’s portfolio page, accessed September 28, 2026, lists the NDP120 as “Mass Production” and identifies audio and sensors as its primary modalities. It lists two package options: a 42-ball WLBGA measuring 3.1 mm × 2.5 mm, and a 40-pin QFN measuring 5 mm × 5 mm. Confirm package details and electrical requirements against the current product brief or datasheet before committing to a board design. Syntiant’s current processor portfolio
Rank #4
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At launch in January 2021, Syntiant said the NDP120 was sampling, planned production-volume shipments for summer 2021, and quoted $6 per unit at a 10,000-unit quantity. Those are historical launch terms, not a current retail price or quotation. Current inventory and pricing are not established by the cited portfolio page; contact Syntiant or its listed sales and distribution channels for a current quote.
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For developers, Syntiant identifies several NDP120-based platforms. Arduino’s Nicla Voice is built with and powered by the NDP120 for always-on edge speech recognition and concurrent AI models. Syntiant also lists an evaluation kit based on a Neural Decision Processor attached to a Raspberry Pi Model 3B+, and the RASynBoard, developed with Avnet and Renesas, which features an NDP120, Renesas RA6M4 host MCU and DA16600 Wi-Fi/Bluetooth module. The portfolio page establishes these product relationships, but does not establish current stock, exact bundle contents or marketplace availability. Syntiant’s portfolio and platform listings
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In a July 2021 announcement, Syntiant and Renesas described a voice-controlled multimodal design combining NDP120 with Renesas RZ/V vision processing for possible uses including cameras, checkout systems, conference equipment and appliances. The release said the reference design, circuit diagrams and bill of materials were then available; it does not establish that the design is currently supported or available. Renesas and Syntiant’s multimodal AI announcement
When the NDP120 is a fit
The NDP120 is most relevant when a product needs local, always-on audio or sensor inference within tight power and space constraints, and its supported networks, interfaces and development path match the design. Its 25× tensor-throughput claim is useful context when comparing Core 2 with Syntiant’s earlier Core 1, but it is not a substitute for testing the intended model and complete system. For procurement or product selection, verify current technical documentation, board availability and pricing directly with the relevant supplier.
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