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Lenovo

Lenovo ThinkPad P53 laptop i7-9750H 32GB 2TB NVME Quadro T1000 15.6" FHD

SKU CH-4SEG-GK1HD

A 15.6" FHD IPS mobile workstation with a 6-core i7-9750H up to 4.5 GHz, 32 GB DDR4, 2 TB NVME and Quadro T1000 4 GB graphics

  • ColorBlack
  • Other FeaturesFingerprint reader
  • Operating SystemWindows 10 Pro
  • CPU TypeIntel Core i7
  • Processor Name2.60 GHz
  • Turbo Frequency4.5
  • Hexa-core i7-9750H turbo to 4.5 GHz for fast render throughput
  • 32 GB DDR4 plus 2 TB NVME handles large datasets without swapping
  • NVIDIA Quadro T1000 4 GB certified for professional 3D and CAD apps
  • 6 inch FHD IPS 500 nits 72% gamut gives accurate colour on site
  • Windows 10 Pro with fingerprint reader and dTPM protects business data

Mobile workstation for rendering and AI

The Lenovo ThinkPad P53 is a mobile workstation built around a 2.60 GHz Intel Core i7-9750H with 12MB cache and 4.5 GHz turbo frequency across 6 cores. It carries 32GB of DDR4 memory and a 2TB NVME drive. The 15.6" FHD IPS panel shows 1920 x 1080 resolution with 500 nits brightness. An NVIDIA Quadro T1000 with 4 GB video memory handles graphics workloads. Windows 10 Pro 64-bit is pre-installed. A fingerprint reader adds biometric sign-in.

Practical limits of the Quadro T1000 GPU

The NVIDIA Quadro T1000 provides 4 GB of dedicated video memory for professional applications. This capacity suits entry-level 3D modelling, CAD and light rendering tasks. Complex scenes with heavy texture loads or large frame buffers will exceed the available VRAM. The GPU is not designed for high-end real-time ray tracing or deep-learning training workloads that demand greater memory bandwidth and compute throughput.

Straightforward setup with single-drive constraint

Windows 10 Pro boots to a ready desktop so the system is productive immediately. The 2TB NVME drive appears as a single volume; no RAID configuration is required. The 32GB DDR4 complement fills the available slots, so future memory expansion means replacing modules rather than adding them. The fingerprint reader enrolls through Windows Hello in seconds. Buyers who want more storage must add external drives or replace the internal NVME module.

特長

  • Hexa-core i7-9750H turbo to 4.5 GHz for fast render throughput
  • 32 GB DDR4 plus 2 TB NVME handles large datasets without swapping
  • NVIDIA Quadro T1000 4 GB certified for professional 3D and CAD apps
  • 6 inch FHD IPS 500 nits 72% gamut gives accurate colour on site
  • Windows 10 Pro with fingerprint reader and dTPM protects business data

仕様

BrandThinkPad
SeriesP53
ModelThinkpad
Part Number20QN
ColorBlack
Other FeaturesFingerprint reader
Operating SystemWindows 10 Pro
CPU TypeIntel Core i7
Processor Name2.60 GHz
Turbo Frequency4.5
Number of Cores6-core Processor
CPU L2 Cache12MB
Screen Size15.6"
TouchscreenNon-Touch Screen
Wide Screen SupportYes
Display TypeFHD
Resolution1920 x 1080
Display FeaturesIn-plane Switching (IPS) Technology
GPU/VPUNVIDIA Quadro T1000
Video Memory4 GB
SSD2TB PCIe
HDDNo
Storage Spec2 TB NVME
Memory32 GB
Memory SpeedDDR2666
LAN10/100/1000Mbps
WLAN802.11ax Wireless LAN
BluetoothBluetooth 5.1
USB2
Video Port1 x HDMI
HDMI1 x HDMI 2.0
Audio Ports1 x Headphone/Microphone Combo Jack
AudioIntegrated Sound card
SpeakerIntegrated Stereo Speakers
TouchpadThinkPad UltraNav
Backlit KeyboardBacklit
WebcamYes
Card Reader4-in-1
TypeWorkstation
AC Adapter/Charger170-watt AC Adapter
BatteryLithium Polymer
Dimensions (W x D x H)14.86x9.93x0.96
Weight5 - 5.9 lbs.

この商品に関する質問

Is the 32GB DDR4 and 2TB NVME enough for heavy rendering and AI workloads?

The 32GB DDR4 and 2TB NVME handle large datasets and project files, while the 6-core i7-9750H up to 4.5GHz and Quadro T1000 4GB GPU accelerate rendering and AI tasks.

What does the 4.5GHz turbo frequency deliver in daily workstation use?

The i7-9750H reaches 4.5GHz on short bursts, speeding single-threaded CAD operations and compile times before thermals settle at the 2.60GHz base across six cores.

How does the NVME interface affect real-world file transfers?

The 2TB NVME drive provides fast sequential read and write speeds, reducing load times for large 3D scenes, video timelines, and machine-learning datasets.

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