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AMD Radeon AI PRO R9700 32GB Specs, Benchmarks & Pricing

The AMD Radeon AI PRO R9700 is a professional AI workstation GPU released on July 23, 2025, built on AMD's RDNA 4 architecture using the Navi 48 GPU die manufactured on TSMC's 4nm process. Featuring 64 compute units with 4,096 stream processors and 128 second-generation AI Accelerators, the card is designed for local AI inference, model fine-tuning, and complex creative workloads. It includes 32GB of high-speed GDDR6 memory on a 256-bit interface running at 20 Gbps, delivering 640 GB/s of memory bandwidth. The GPU delivers 47.8 TFLOPS of FP32 vector performance and 95.7 TFLOPS of FP16 vector performance, with clock speeds ranging from 1,620 MHz base to 2,920 MHz boost (game clock of 2,350 MHz). The 2nd-generation AI Accelerators deliver 191 TFLOPS FP16 matrix, 383 TOPS INT8 matrix, and 766 TOPS INT4 matrix (dense), with structured sparsity doubling throughput to 383 TFLOPS FP16, 766 TOPS INT8, and 1,531 TOPS INT4. The card features a compact dual-slot design with a blower-style cooling solution and a 300W TDP, using PCIe 5.0 connectivity for maximum bandwidth. AMD positions this as their flagship AI workstation GPU, fully compatible with the ROCm open software platform with support for PyTorch, ONNX Runtime, and TensorFlow frameworks. Display connectivity includes four DisplayPort 2.1 outputs. Available initially in SI-built workstation systems from Boxx and Velocity Micro, with standalone cards from ASRock, ASUS, Gigabyte, PowerColor, Sapphire, XFX, and Yeston available later in Q3 2025. Priced at $1,299 USD, it targets AI developers, data scientists, and creative professionals who need substantial local AI inference capability.

Release Date: July 23, 2025
MSRP: $1,299 USD
GPU Architecture: RDNA 4
Hardware-Accelerated GEMM Operations:
FP16 FP32 BF16 FP8 INT8 INT4 TF32 FP64 INT1
CUDA Compute Capability : n/a

Strengths

Excellent memory capacity (top 9% of GPUs)
Excellent INT8 inference performance (top 18% of GPUs)
Strong 3DMark Wild Life Extreme (4K) performance (top 23% of GPUs)
Strong 3DMark Wild Life Extreme (1440p) performance (top 16% of GPUs)

Specifications for AMD Radeon AI PRO R9700

Specification	Performance Ranking
FP32 TFLOPs	73rd @ 47.8 TFLOPs (Mid Tier)(Mid)
FP16 TFLOPs	53rd @ 95.7 TFLOPs (Mid Tier)(Mid)
Tensor Core Count	33rd @ 128 Cores (Entry Tier)(Entry)
Memory Capacity (GB)	91st @ 32 GB (Top Tier)(Top)
Memory Bandwidth (GB/s)	65th @ 640 GB/s (Mid Tier)(Mid)
Int8 TOPs	82nd @ 383 TOPs (Top Tier)(Top)

Gaming Benchmarks for AMD Radeon AI PRO R9700

Rankings based on 692 real-world benchmark results from OpenBenchmarking.org

Benchmark	Performance Ranking
3DMark Wild Life Extreme (4K)	77th @ 273 FPS (Top Tier)(Top)
3DMark Wild Life Extreme (1440p)	84th @ 552 FPS (Top Tier)(Top)

Real-time AMD Radeon AI PRO R9700 GPU Prices

We're tracking 8 of the AMD Radeon AI PRO R9700 GPUs currently available for sale. The lowest average price is $1,535 (what's this?)

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Price History

This chart tracks AMD Radeon AI PRO R9700 prices over the past 6 months based on eBay listings. The green line shows the median price across all listings each day, while the yellow line shows the average of the three lowest-priced listings—a useful indicator for finding deals.

Trend: Over this period, the lowest average price has been down 23.5%. The current lowest average is $1,535, compared to a typical $2,042 over the period. The lowest average price is calculated as the average of the three lowest-priced listings each day.

gpupoet.com

Product Identifiers

Manufacturer Part Numbers (1)

AMD OPN: 100-300000008

Available from 4 Partners (4 products)

XFX

XFX AMD Radeon AI Pro R9700 32GB GDDR6 4xDP: RX-97XPROAIY(model number)

ASRock

ASRock AMD Radeon AI PRO R9700 Creator 32GB GDDR6: R9700 CT 32G(model number)

PowerColor

PowerColor Radeon AI PRO R9700 32GB: AXAIRPR9700 32GBDP(model number)

Sapphire

Sapphire Radeon AI PRO R9700 32GB: 32358-01-20G(model number)

References

Notes

MSRP of $1,299 USD sourced from AMD official blog post and retail listings. Available July 23, 2025 in SI-built systems, with standalone cards from board partners available later in Q3 2025.
FP32 TFLOPS of 47.8 calculated as 4,096 stream processors × 2,920 MHz boost clock × 4 ops/cycle (dual-issue) ÷ 1,000,000 = 47.8 TFLOPS. RDNA 4 architecture features dual-issue FP32 capability, effectively doubling shader throughput compared to single-issue designs.
FP16 TFLOPS of 95.7 is the peak FP16 vector (shader) performance per the AMD official datasheet (radeon-ai-pro-r9700-datasheet.pdf). FP16 matrix performance via AI Accelerators is 191 TFLOPS dense, 383 TFLOPS with structured sparsity.
INT8 TOPS of 383 is the peak INT8 matrix (dense) performance per the AMD official datasheet. With structured sparsity, INT8 reaches 766 TOPS. INT4 matrix is 766 TOPS dense, 1,531 TOPS sparse. FP8 matrix is 383 TFLOPS dense, 766 TFLOPS sparse.
tensorCoreCount of 128 represents the 2nd-generation AI Accelerators (2 per compute unit × 64 compute units), which are AMD's dedicated matrix multiplication units for AI workloads.
Memory bandwidth calculated as 256-bit interface × 20 Gbps ÷ 8 bits/byte = 640 GB/s, confirmed by AMD specifications.
RDNA 4 architecture includes redesigned 3rd-generation Ray Tracing Accelerators and 2nd-generation AI Accelerators with support for sparsity acceleration.
Supported hardware operations include FP8, FP16, BF16, INT8, and INT4 on AI Accelerators, with FP32 operations on general shader units. Sparsity acceleration enables up to 4× FP16 and 8× INT8 throughput.
The GPU uses the Navi 48 GPU die manufactured on TSMC's 4nm process with 64 Compute Units.
Clock speeds specified by AMD as Base Clock 1,620 MHz, Game Clock 2,350 MHz, Boost Clock up to 2,920 MHz.
Board partners include ASRock, ASUS, Gigabyte, PowerColor, Sapphire, XFX, and Yeston. Part numbers sourced from XFX official product page and third-party retail listings.
The card features a compact dual-slot design with blower-style cooling, four DisplayPort 2.1 outputs, and PCIe 5.0 x16 interface.
AMD positioning emphasizes ROCm platform compatibility with PyTorch, ONNX Runtime, TensorFlow, and other AI/ML frameworks for local AI inference and model fine-tuning workloads.
System integrators offering workstations with R9700 include Boxx and Velocity Micro at launch.