SiMa.ai Raised $150 Million for AI Chip Development
The edge AI hardware startup has secured capital to build its third-generation silicon platform by 2028.
Updated on Sept. 28, 2026 in Semiconductors
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SiMa.ai has raised $150 million in new funding, pushing the company valuation to $1.4 billion. The capital will support the development of a third-generation platform designed to handle edge AI workloads.
Why it matters
As compute demand shifts toward physical devices, the ability to pack high-performance AI processing into low-power hardware is becoming the primary metric for market viability. This funding accelerates SiMa.ai's trajectory toward deploying its silicon into power-constrained environments like automotive systems.
The company targets a performance level of 1,000 tera operations per second (TOPS) at an 80-watt power envelope for its future platform. This aims to build on their existing software stack, Palette Neat, which manages AI model optimization for silicon.
The players
SiMa.ai
A startup developer of edge AI silicon and software platforms for local device compute.
Fidelity Management & Research Company
A global investment firm that co-led this funding round.
Amplify Partners
A venture capital firm specializing in early-stage data and AI infrastructure that co-led the round.
The details
SiMa.ai builds purpose-built silicon and software to run artificial intelligence models locally on devices rather than in the cloud. Their approach utilizes a specialized software platform, Palette Neat, to compile and optimize neural networks—mathematical models modeled on the human brain—to run efficiently on their proprietary hardware. The company currently employs 170 engineers out of a 200-person total staff to focus on these chip and software development workflows.
Timeline
Revenue grew fourfold between 2024 and 2025.
The third-generation platform is scheduled for release in the first half of 2028.
The Tech Race
SiMa.ai is positioning itself against established silicon providers by focusing specifically on the power-to-performance ratio required for edge deployment. This funding round tracks the industry-wide transition toward specialized architectures that bring large model capabilities onto constrained physical devices.
Automotive manufacturers and industrial operators will be the primary early adopters of these third-generation chips. While consumers will not interact with the silicon directly, the hardware will enable more complex AI features to run inside vehicles without relying on cloud-based latency.
The takeaway
The race for efficient edge AI remains focused on achieving massive TOPS counts within extremely low power constraints. Watch for the official performance benchmarks of the third-generation platform as the 2028 release date approaches.
What happens next
The company expects to launch its third-generation platform during the first half of 2028.
Further reading
For more on the current landscape of specialized compute, visit Semiconductors.
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