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Station - Company Ranking(44 companyies in total)

Last Updated: Aggregation Period:Aug 13, 2025〜Sep 09, 2025
This ranking is based on the number of page views on our site.

Company Name Featured Products
Product Image, Product Name, Price Range overview Application/Performance example
OS: Not selected ⇒ If you have a preferred OS, please consult with us! We will provide a separate estimate. CPU: Intel Xeon Silver 4514Y (16C/32T) Memory: 256GB (16GB×16) DDR5-4800 Registered ECC DIMM SSD: 960GB SATA3-SSD (using Samsung PM893) GPU: NVIDIA T400 4GB-GDDR6 Power Supply: 1500W/200V (1200W/100V) 80Plus Platinum certified Motherboard: C741 chipset Warranty: 3-year send-back repair warranty Included Accessories: Mouse, Keyboard An integrated package of open-source code for electronic structure calculations and nanoscale material design, QUANTUM ESPRESSO applications.
"HALCON 25.05" compatible workstation
"HALCON 25.05" compatible workstation

1 million yen-5 million yen

- Be-Clia Type-TU2-9 equipped with NVIDIA RTX4500 Ada BTO Hardware performance that maximizes the benefits of new features such as Deep Learning Inference Optimizer and acceleration of 3D toolsets. The combination of Ada generation GPU + DDR5 high-speed memory + Core Ultra architecture significantly improves the processing throughput of HALCON. It can also meet on-site implementation requirements such as "high-speed processing of high-resolution camera images," "real-time inference," and "simultaneous processing of multiple cameras." - CERVO Grasta Type-ALIS25WC-W5 equipped with NVIDIA RTX6000 Ada workstation Large-capacity memory and high-bandwidth memory allow for ample parallel processing. In multi-threaded and multi-object processing, the memory bandwidth is less likely to become a bottleneck. Supports deep learning training with RTX 6000 Ada. Both training and inference are accelerated in HALCON's Deep Learning extension module. HALCON Progress Edition 25.05 is an image processing library that is globally utilized in the field of machine vision. The latest version further enhances deep learning-based appearance inspection and defect detection capabilities, with numerous implementations for high-precision appearance inspection and pattern matching in industries such as semiconductors, electronic components, and automotive. Its high-speed and robust processing performance also supports real-time processing on production lines. Additionally, the acceleration of learning and inference through GPU contributes to the efficiency of AI inspections.
Main Specifications BT-U7265KAS1N1TTNVM ・CPU: Intel Core Ultra 7 265 20C (P8+E12) 20T Pcore: 2.4~5.2GHz ・Memory: 256GB (64GB x4) DDR5-6400 ・SSD: 1TB (M.2 NVMe) R: 5150MB/s | W: 4900MB/s ・OS: Windows 11 Pro ・GPU: NVIDIA GeForce RTX 5070 Ti 16GB-GDDR7 BT-U9285KAS1N2TTNVM ・CPU: Intel Core Ultra 9 285K 24C (P8+E16) 24T Pcore: 3.7~5.5GHz ・Memory: 256GB (64GB x4) DDR5-6400 ・SSD: 2TB (M.2 NVMe) R: 7300MB/s | W: 6600MB/s ・OS: Windows 11 Pro ・GPU: NVIDIA GeForce RTX 5090 32GB-GDDR7 Main uses - 2D/3D image analysis - Deep learning - AI development, inference - Simulation
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  1. Featured Products
    Recommended Workstation for QUANTUM ESPRESSORecommended Workstation for QUANTUM ESPRESSO
    overview
    OS: Not selected ⇒ If you have a preferred OS, please consult with us! We will provide a separate estimate. CPU: Intel Xeon Silver 4514Y (16C/32T) Memory: 256GB (16GB×16) DDR5-4800 Registered ECC DIMM SSD: 960GB SATA3-SSD (using Samsung PM893) GPU: NVIDIA T400 4GB-GDDR6 Power Supply: 1500W/200V (1200W/100V) 80Plus Platinum certified Motherboard: C741 chipset Warranty: 3-year send-back repair warranty Included Accessories: Mouse, Keyboard
    Application/Performance example
    An integrated package of open-source code for electronic structure calculations and nanoscale material design, QUANTUM ESPRESSO applications.
    "HALCON 25.05" compatible workstation"HALCON 25.05" compatible workstation
    overview
    - Be-Clia Type-TU2-9 equipped with NVIDIA RTX4500 Ada BTO Hardware performance that maximizes the benefits of new features such as Deep Learning Inference Optimizer and acceleration of 3D toolsets. The combination of Ada generation GPU + DDR5 high-speed memory + Core Ultra architecture significantly improves the processing throughput of HALCON. It can also meet on-site implementation requirements such as "high-speed processing of high-resolution camera images," "real-time inference," and "simultaneous processing of multiple cameras." - CERVO Grasta Type-ALIS25WC-W5 equipped with NVIDIA RTX6000 Ada workstation Large-capacity memory and high-bandwidth memory allow for ample parallel processing. In multi-threaded and multi-object processing, the memory bandwidth is less likely to become a bottleneck. Supports deep learning training with RTX 6000 Ada. Both training and inference are accelerated in HALCON's Deep Learning extension module.
    Application/Performance example
    HALCON Progress Edition 25.05 is an image processing library that is globally utilized in the field of machine vision. The latest version further enhances deep learning-based appearance inspection and defect detection capabilities, with numerous implementations for high-precision appearance inspection and pattern matching in industries such as semiconductors, electronic components, and automotive. Its high-speed and robust processing performance also supports real-time processing on production lines. Additionally, the acceleration of learning and inference through GPU contributes to the efficiency of AI inspections.
    Core Ultra × 256GB Memory [Large Capacity at a Low Price]Core Ultra × 256GB Memory [Large Capacity at a Low Price]
    overview
    Main Specifications BT-U7265KAS1N1TTNVM ・CPU: Intel Core Ultra 7 265 20C (P8+E12) 20T Pcore: 2.4~5.2GHz ・Memory: 256GB (64GB x4) DDR5-6400 ・SSD: 1TB (M.2 NVMe) R: 5150MB/s | W: 4900MB/s ・OS: Windows 11 Pro ・GPU: NVIDIA GeForce RTX 5070 Ti 16GB-GDDR7 BT-U9285KAS1N2TTNVM ・CPU: Intel Core Ultra 9 285K 24C (P8+E16) 24T Pcore: 3.7~5.5GHz ・Memory: 256GB (64GB x4) DDR5-6400 ・SSD: 2TB (M.2 NVMe) R: 7300MB/s | W: 6600MB/s ・OS: Windows 11 Pro ・GPU: NVIDIA GeForce RTX 5090 32GB-GDDR7
    Application/Performance example
    Main uses - 2D/3D image analysis - Deep learning - AI development, inference - Simulation