AI Server for development teams and organizations
AI Server WorkstationEnterprise-grade AI workspace
Dell Precision 7875 Tower
NVIDIA RTX PRO 6000 Blackwell Max-Q
A tower workstation base platform with GPU configuration guidance for model development, data processing, and 3D graphics work. Choose the CPU, RAM, and storage to match your team's software and workload.
700,000 THB
A starting budget for project evaluation. The model variant, number of GPUs, CPU, RAM, SSD, software, installation work, tax, and warranty are confirmed in the quotation.Confirm sourcing and the delivery schedule before ordering. The reference model is no longer available for sale in some countries.
References the RTX PRO 6000 Blackwell Max-Q Workstation Edition 300 W, per the option Dell lists for this model. A compatible component set must be confirmed before ordering.
Match compute power to the workload
Example workloads for evaluation. The actual models, software, and data must be tested before confirming speed or the number of concurrent users.
LLMs and enterprise knowledge
Develop and evaluate language models, connect document retrieval to compose answers, and define data access rights for each team.
See Enterprise KM ChatbotAI Vision and image data
Trial model learning on sample images, check data quality, and measure results before deploying to cameras or on-site systems.
See Machine Vision services3D and simulation work
Evaluate rendering, simulation, and image datasets alongside AI workloads, while verifying the software and licenses required.
Consult on system design
Dell Precision 7875 Tower
A hardware baseline for designing the configuration that fits you
This list shows the platform and reference options; it is not the full list of components included in the starting price.
Check manufacturer specs
Dell Precision 7875NVIDIA RTX PRO 6000 Max-Q- Chassis
- Dell Precision 7875 Tower
- CPU platform
- AMD Ryzen Threadripper PRO · Model and core count selected by workload
- Reference GPU
- NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition
- GPU memory
- 96 GB GDDR7 ECC · Separate from host RAM
- GPU power
- 300 W is the power of the card, not the total power draw of the system
- Host RAM
- DDR5 ECC RDIMM · Capacity and module layout per the quotation
- Storage
- NVMe SSD · Capacity sized from data, models, and backups
- Operating system
- Windows or Linux, depending on compatibility and the licenses selected
- Power and cooling
- Check the PSU, power cabling, BIOS, and cooling against the selected GPU configuration
Choose the AI Server that fits your team's starting point
Compare system formats and initial budgets, then evaluate against your actual models and software. The shared memory of DGX Spark and the VRAM of RTX PRO are different approaches, so capacity figures alone cannot determine speed.
Compact AI Server
NVIDIA DGX Spark
Indicative starting price 300,000 THBView details for this modelAI Server Workstation
Dell Precision 7875 Tower
Indicative starting price 700,000 THBView details for this modelQuestions to settle before configuring the workstation
Is the approximate 700,000 THB starting price a fixed specification?
It is a starting budget used to evaluate the project. The model variant, CPU, GPU, RAM, SSD, software, installation work, tax, warranty, and delivery schedule must be confirmed in the quotation. Additional hardware or services are not considered included automatically.
How does this RTX PRO 6000 differ from the RTX 6000 Ada?
This offer references the RTX PRO 6000 Blackwell Max-Q with 96 GB GDDR7 ECC memory, which is a different product from the RTX 6000 Ada. Selecting a system requires stating the full model name and checking compatibility, not relying on the name RTX 6000 alone.
Can GPUs be added or RAM expanded later?
Slot space, PCIe lane count, power, power cabling, cooling, and software support for that configuration must be checked first. The starting price is not considered to include multiple GPUs, nor is the memory of multiple cards assumed to combine for every workload.
Can it be used as an AI Server for many people in the organization?
It can be evaluated for delivery over the network, with user accounts, job queuing, data permissions, and system administration designed accordingly. The number of users and response times must be tested with real models and workloads before being confirmed.
Do you already have an AI task you want to start?
Send us sample work and your team's requirements for us to assess, so the unit and system scope match real use.