Company comparison
Quadric vs FuriosaAI
Radar profile, momentum bars, and stack placement side by side.
Quadric
Not scored
momentum
FuriosaAI
Not scored
momentum
Quadric capital
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FuriosaAI capital
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No radar series.
Momentum head-to-head
Attribute tape
| Field | Quadric | FuriosaAI |
|---|---|---|
| Category | Semiconductors and hardware | Semiconductors and hardware |
| Stack | Layer 1 | Layer 1 |
| HQ | Burlingame, CA, United States | Seoul, South Korea |
| Founded | 2016 | 2017 |
| Status | Operating | Operating |
| Funding | — | — |
| Momentum | — | — |
| Summary | Quadric licenses the Chimera GPNPU, a programmable AI processor IP for on-device inference that unifies scalar, vector, and matrix workloads so chip designers can run ML inference and traditional control/DSP code on a single architecture without separate CPUs or NPUs. | FuriosaAI is a South Korean fabless semiconductor company that designs AI inference accelerators (NPUs) for data-center workloads, including large language models and computer vision. Its hardware-software co-design approach — anchored by the proprietary Tensor Contraction Processor (TCP) architecture and RNGD accelerator family — targets high performance per watt and per dollar as an alternative to GPU-centric AI infrastructure. |
| Who for | Teams evaluating AI vendors in this category. | Teams evaluating AI vendors in this category. |
| Differentiator | Quadric licenses the Chimera GPNPU, a programmable AI processor IP for on-device inference that unifies scalar, vector, and matrix workloads so chip designers can run ML inference and traditional control/DSP code on a single architecture without separate CPUs or NPUs. | FuriosaAI is a South Korean fabless semiconductor company that designs AI inference accelerators (NPUs) for data-center workloads, including large language models and computer vision. Its hardware-software co-design approach — anchored by the proprietary Tensor Contraction Processor (TCP) architecture and RNGD accelerator family — targets high performance per watt and per dollar as an alternative to GPU-centric AI infrastructure. |