Power up your productivity, gaming, and content creation with the Intel Core i7-13700KF 3.4 GHz 16-Core LGA 1700 Processor. This 13th generation desktop processor builds upon the Hybrid Core architecture and Intel 7 process by fitting 16 cores— four more than the previous generation— onto a single processor while still fitting the LGA 1700 socket. Designed to provide high performance, the Core i7-13700KF features eight low-voltage Efficient-cores that handle background tasks for multitasking while the eight 3.4 GHz Performance-cores provide speed for demanding applications and games. The built-in Intel Thread Director ensures that the two work seamlessly together by dynamically and intelligently assigning workloads to the right core at the right time.

With 30MB of cache and a 5.4 GHz Turbo Boost Max 3.0 frequency, this processor is made to handle intense workloads. You can also overclock this processor for even greater performance. The Core i7-13700KF also supports PCI Express 5.0 and dual-channel DDR5 memory at 5600 MHz.

The Core i7-13700KF does t include integrated graphics, meaning that users will need to purchase a separate dedicated graphics card. This processor is backed by a 3-year warranty.

Hybrid Core Design
Performance-cores provide the speed to handle high-end games and demanding applications while low-priority and background tasks are handled by the processor’s Efficient-cores for multitasking.

Intel Thread Director
The Intel Thread Director is built into the CPU’s cores, working with the operating system to ensure each of the 24 threads are assigned to the right core at the right time.

PCIe 4.0 & 5.0
This processor supports up to four PCIe 4.0 and sixteen PCIe 5.0 lanes, delivering 20 lanes in total for exceptional data throughput with compatible devices.

Gaussian & Neural Accelerator 3.0
Gaussian and Neural Accelerator 3.0 (GNA) techlogy helps with ise suppression while enhancing background blurring during video chats.

Intel Deep Learning Boost
Accelerates AI inference to improve performance for deep learning workloads.