Power up your productivity, gaming, and content creation with the Intel Core i5-14400 2.5 GHz 10-Core LGA 1700 Processor.
Built with the Intel 7 process, this 14th generation desktop processor
delivers improved power efficiency while fitting the LGA 1700 socket.
Featuring an optimized Hybrid Core Architecture, the Core i5-14400
powers applications and games with six 2.5 GHz Performance-cores while
the four low-voltage Efficient-cores handle background tasks for smooth
multitasking. 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 20MB of cache and a 5 GHz Turbo Boost frequency, this processor is
made to handle a variety of workloads. The Core i5-14400 also supports
PCI Express 5.0 and up to 192GB of dual-channel DDR5 memory at 4800 MHz.
The Core i5-14400 features integrated Intel UHD 730 Graphics. A Laminar RM1 cooler is included.
Hybrid Core Design
Performance-cores
provide the speed to handle high-end games and demanding applications
while low-priority and background tasks such as streaming video, playing
music, and encoding media are handled by the processor's
Efficient-cores.
Intel Thread Director
The
Intel Thread Director is built into the CPU's cores, working with the
operating system to ensure each of the 16 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.
Integrated Graphics
The
integrated Intel UHD 730 Graphics delivers rich 3D performance for
high-quality visuals with support for either one 7680 x 4320 resolution
8K monitor or up to four 3840 x 2160 resolution 4K displays.
Gaussian & Neural Accelerator 3.0
Gaussian
and Neural Accelerator 3.0 (GNA) technology helps with noise
suppression while enhancing background blurring during video chats.
Intel Deep Learning Boost
Accelerates AI inference to improve performance for deep learning workloads.