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Technology

Dell Targets AI-Ready Professionals With New Pro Precision Range in India

Dell's newly launched Pro Precision workstation portfolio in India spans five product lines and two AI-accelerator systems, with pricing from Rs 89,000 to Rs 4,99,000.

Dell is betting on demand from India’s AI-focused engineering and design workforce with the launch of its Pro Precision workstation portfolio, a five-line range that runs from an entry-level desktop tower to ultra-thin mobile workstations built for heavy rendering and simulation work.

Pricing starts at Rs 89,000 for the Pro Precision 7 T1 desktop, which uses Intel Core Ultra Series 2 processors paired with a dedicated NPU for on-device AI tasks. The mobile lineup then splits into two tiers, the 5 series and the 7 series, both available in 14-inch and 16-inch builds.

Dell is pitching the Pro Precision 5 series 14S as its thinnest and lightest workstation ever built, weighing 1.4kg with a three-sided aluminium chassis. Buyers can choose Intel Core Ultra Series 3 chips with integrated Arc Pro graphics or AMD Ryzen AI 400 processors with Radeon PRO graphics, with support for up to 64GB of 8533 MT/s LPCAMM2 memory; it ships from August 10.

The standard 5 series, priced from Rs 1,49,000, runs Intel Core Ultra 9 Series 3 chips with a 50 TOPS NPU and configurable NVIDIA RTX 500 or RTX Pro 2000 Blackwell graphics. The 7 series moves further upmarket at Rs 2,25,000 and up, with the 16-inch model offering 50W processors, the same 50 TOPS NPU, RTX Pro 3000 Blackwell graphics and storage up to 8TB.

Beyond the core workstation range, Dell has introduced Pro Max, a two-tier AI-accelerator line. The GB10 configuration, aimed at individual agent prototyping, is priced from Rs 4,99,000 and is available immediately, while the GB300 configuration, built for frontier-scale AI model inference, is slated for a later 2026 launch. Dell has also added Wi-Fi 7, optional 5G, Thunderbolt 4 and FIPS 140-3-certified TPM 2.0 security across the range, along with EPEAT Gold and ENERGY STAR credentials on select models.

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