AMD has announced that its workstation-class graphics card, based on the innovative RDNA 4 architecture — the Radeon AI Pro R9700 — will be available on October 27, 2025, with an official suggested retail price of $1,299. This graphics card was initially revealed at this year's Computex in Taipei, and it has taken considerable time to finalize both the release date and pricing. The pricing confirms earlier market rumors; it is almost double the cost of the gaming flagship RX 9070 XT, but it is designed for more specialized AI computing tasks.

The Radeon AI Pro R9700 leverages the RDNA 4 architecture and employs the Navi 48 GPU. It shares the same core configuration as the RX 9070 XT, including 4,096 stream processors, 128 Rendering Output Units (ROPs), and the same number of Ray Tracing Units (RT Core). However, the significant differences lie in its memory capacity and optimization focus: the R9700 boasts 32GB of GDDR6 memory, linked through a 256-bit memory bus with extensive bandwidth optimized for local AI training and inference tasks. In comparison, the RX 9070 XT possesses only half the memory capacity. AMD highlights the R9700 as "the most cost-effective 32GB workstation GPU" available.

Unlike consumer graphics cards, the Radeon AI Pro R9700 is not offered in a reference model and will be sold exclusively through AMD's partner channels, including brands such as ASRock and Sapphire. Certain models will only be available to system integrator (SI) customers. The ASRock Creator Radeon AI Pro R9700 has surfaced in select retailer listings, briefly priced around $1,329, aligning with official pricing. Visibly, the R9700 features a dual-slot design with a blower-style cooling solution suitable for multi-GPU parallel configurations, optimized for efficient cooling and airflow in multi-GPU environments.

AMD emphasizes that the Radeon AI Pro R9700 is not merely a graphics processor but a workstation-class accelerator card capable of executing AI models locally. With the ROCm open software platform's support, it can accelerate large language models (LLMs), diffusion models, and various generative AI workloads within desktop environments, delivering a nearly datacenter-grade computational experience. According to AMD's official data, the card's performance is double that of the Radeon Pro W7800 on DeepSeek R1 models, enabling effective execution of text-generated images on desktop platforms. ROCm's multi-GPU scaling further enables users to construct high-throughput AI training environments on a single machine, with memory configured linearly for handling more intricate model deployments.

The introduction of the Radeon AI Pro R9700 indicates AMD's push to extend AI inference and training capabilities from servers to local workstations. In the past year, workstation GPUs have emerged as a new market focal point with the increasing demand for generative AI and local model execution. With a memory advantage over high-end consumer cards like NVIDIA's RTX 5080, which only offers 16GB, the R9700 proves its worth in scenarios requiring medium to large AI model loads. AMD claims that this card can undertake LLM inference tasks independently of cloud resources, making it ideal for professionals in content creation, AI development, and scientific research fields.

Notably, the R9700 is a component of AMD's custom AI GPU strategy, demonstrating the company's gradual expansion into the professional computing market. By integrating gaming and AI capabilities onto the same GPU core, AMD endeavors to address a comprehensive range of computing needs, from desktop to datacenter, within a unified architectural system. This strategy is mirrored by AMD's Instinct series on the server side (e.g., MI400, MI500), forming a cohesive AI-accelerated ecosystem spanning personal workstations to high-performance clusters.

With the debut of the Radeon AI Pro R9700, AMD has taken a pivotal step forward in AI localization computing. This release provides creators and small- to medium-sized businesses (SMBs) with a relatively accessible platform featuring substantial graphics memory and sets the foundation for subsequent RDNA 5 and XDNA NPU strategies. As AI models become more mainstream on the workstation front, the R9700 could play a crucial role in normalizing "desktop AI computing."