AMD unleashes Radeon AI PRO R9700S with massive 32GB memory and silent passive cooling for high-density AI workloads
- AMD Radeon AI PRO R9700S delivers 47.8 TFLOPS maximum FP32 computing power
- AMD equips the R9700S with 32GB of GDDR6 memory for AI workloads
- PCIe 5.0 x16 support enables high-bandwidth communication for AI applications
AMD introduced the Radeon AI PRO R9700S, a passively cooled workstation GPU that joins the R9000 series and promises enterprise-grade AI performance.
Following the launch of this series earlier this year, several major brands have confirmed R9700 cards, indicating strong industry adoption.
The R9700S retains the same Navi 48 RDNA4 configuration as the standard R9700, offering 64 compute units and 4096 stream processors.
Passive cooling for high-density AI workloads
Its boost clock reaches up to 2920 MHz and delivers a peak FP32 throughput of 47.8 TFLOPS, making it a high-performance option for enterprise AI workloads.
Designed for dense racks and multi-GPU setups, the R9700S uses a 32GB GDDR6 buffer on a 256-bit bus with 64MB Infinity Cache.
PCIe 5.0 x16 support ensures high-bandwidth communication with compatible workstation platforms.
The “S” designation in the R9700S indicates a quiet design, which replaces the fan-style cooler of previous models.
This approach uses system airflow rather than built-in fans, making the GPU suitable for compact racks where multiple cards work closely together.
Despite passive cooling, the card maintains a TDP of 300W and draws power via a single 12V-2×6 connector.
This approach reflects AMD’s focus on maintaining computing performance without adding active components.
The company also launched the R9600D, which can hold up to 48 compute units and 3,072 stream processors while maintaining identical memory.
However, the R9700S offers higher throughput for large AI models.
Both cards support Linux ECC memory options and are fully compatible with AMD’s Software PRO Edition and ROCm integration.
The R9700S is optimized for tasks such as AI generative inference and training large language models.
This allows businesses to offload demanding workloads from CPU cores to GPU accelerators.
Early adoption of the R9700 appeared in prebuilt systems like Elsa’s Veluga-D A70S G6 workstation.
It pairs the GPU with an AMD Ryzen 7 9700X processor, 64GB of DDR5 RAM, and PCIe expansion slots for additional accelerators.
With these chips, AMD offers enterprise solutions for AI computing while focusing on memory bandwidth, power delivery and quiet operation.
That said, this chip’s high raw performance raises questions about sustained thermal performance in dense deployments.
Therefore, companies deploying multiple units must consider system-level airflow and heat management to maintain stability under peak AI workloads.
Via Video cardz
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