NVIDIA's "China-compliant" GeForce RTX 5090D is expected to face new restrictions this time, compromising AI and crypto-mining performance.
NVIDIA's GeForce RTX 5090D Now Prevented From Being Used In Multi-GPU Setups, Keeping Chinese AI Firms Away From It
Team Green has no plans to leave the Chinese consumer markets behind. Alongside the mainstream RTX 50 series, the firm plans to immediately launch the GeForce RTX 5090D, which will be a successor to the RTX 4090D. There were rumors that NVIDIA won't do much in terms of downgrading the specifications of the RTX 5090D, and previous leaks have indeed verified this claim, but new findings from Chiphell reveal that there are some differences, specifically in terms of AI and mining performance of the SKU.
The first major difference lies in the "performance cut-off," specifically in AI and crypto-related applications. It is claimed that after three seconds of workload, the GPU will automatically lock its performance, which likely refers to reduced clock speeds or performance throttling through the onboard software. Yet again, similar to the RTX 4090D, the power limit changes are restricted as well, so for professional computing workloads, the GeForce RTX 5090D may cause troubles in providing optimal performance.
Another interesting difference is that the GeForce RTX 5090D will be barred from being used in multi-GPU configurations, which means that users won't be able to stack multiple SKUs to squeeze out higher performance. This trend was on top with the GeForce RTX 4090D, where individuals would convert it into "blower-style" designs and then use them in AI clusters to get out performance equivalent to that of mainstream AI accelerators. Multi-GPU setups won't be possible with the RTX 5090D anymore, even on Linux, as NVIDIA has implemented extensive restrictions.
For gamers, the new restrictions won't affect performance since they are entirely targeted towards AI and professional workloads. For a quick rundown on the specifications of the GeForce RTX 5090D, it features the GB202 GPU die with a total of 21,760 CUDA Cores, along with 32 GB of GDDR7 memory running at 28 Gbps, offering a total of 1792 GB/s bandwidth. We have already seen AIB models, such as those from GALAX, surface, indicating that the markets are ready.
NVIDIA GeForce RTX 50 GPU Specs (Official):
| Graphics Card Name | NVIDIA GeForce RTX 5090 | NVIDIA GeForce RTX 5080 | NVIDIA GeForce RTX 5070 Ti | NVIDIA GeForce RTX 5070 | NVIDIA GeForce RTX 5060 Ti | NVIDIA GeForce RTX 5060 | NVIDIA GeForce RTX 5050 |
|---|---|---|---|---|---|---|---|
| GPU Name | Blackwell GB202-300 | Blackwell GB203-400 | Blackwell GB203-300 | Blackwell GB205-300 | Blackwell GB206-300 | Blackwell GB206-250 | Blackwell GB207-300 |
| GPU SMs | 170 | 84 | 70 | 48 | 36 | 30 | 20 |
| GPU Cores | 21760 | 10752 | 8960 | 6144 | 4608 | 3840 | 2560 |
| Clock Speeds | 2017 MHz (Base) 2407 MHz (Boost) | 2295 MHz (Base) 2617 MHz (Boost) | 2295 MHz (Base) 2452 MHz (Boost) | 2325 MHz (Base) 2512 MHz (Boost) | 2407 MHz (Base) 2572 MHz (Boost) | 2280 MHz (Base) 2497 MHz (Boost) | 2317 MHz (Base) 2572 MHz (Boost) |
| Memory Capacity | 32 GB GDDR7 | 16 GB GDDR7 | 16 GB GDDR7 | 12 GB GDDR7 | 8-16 GB GDDR7 | 8 GB GDDR7 | 8 GB GDDR6 |
| Memory Bus | 512-bit | 256-bit | 256-bit | 192-bit | 128-bit | 128-bit | 128-bit |
| Memory Speed | 28 Gbps | 30 Gbps | 28 Gbps | 28 Gbps | 28 Gbps | 28 Gbps | 20 Gbps |
| Bandwidth | 1792 GB/s | 960 GB/s | 896 GB/s | 672 GB/s | 448 GB/s | 448 GB/s | 320 GB/s |
| Power Interface | 1 12V-2x6 (16-Pin) | 1 12V-2x6 (16-Pin) | 1 12V-2x6 (16-Pin) | 1 12V-2x6 (16-Pin) | 16-Pin or 8-Pin | 8-Pin | 8-Pin |
| Launch | 30th Jan, 2025 | 30th Jan, 2025 | 20th Feb, 2025 | 4th March, 2025 | 16th April, 2025 | 19th April, 2025 | 1st July, 2025 |
| TBP | 575W | 360W | 300W | 250W | 180W | 145W | 130W |
| Price (MSRP) | $1999 | $999 | $749 | $549 | $379-$429 | $299 | $249 |
About the author: Muhammad Zuhair is a hardware and technology reporter for Wccftech, specializing in the semiconductor industry and the complex interplay between technology, manufacturing, and geopolitics. His coverage focuses on the corporate strategies and technological roadmaps of industry giants like TSMC, NVIDIA, Samsung, and Intel. Zuhair's expertise lies in deconstructing complex topics such as fabrication nodes (e.g., 2nm process), the economic impact of policies like the CHIPS Act, and the strategic development of AI infrastructure from NVIDIA, AMD and Intel.
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