AMD Radeon RX 9070 XT
vs
AMD Radeon AI PRO R9700

vs
AMD Radeon RX 9070 XT vs AMD Radeon AI PRO R9700 graphics card comparison

GPU Comparison Result

AMD Radeon RX 9070 XT vs Radeon AI PRO R9700: Same GPU, but Twice the Memory

The Radeon AI PRO R9700 can easily be mistaken for a significantly more powerful version of the RX 9070 XT. In reality, their computing capabilities are nearly identical: both graphics cards use RDNA 4 architecture, feature 64 compute units, 4096 stream processors, 64 ray tracing accelerators, and 128 AI accelerators. Moreover, the gaming model operates at a slightly higher frequency.

The main difference lies in the amount of video memory. The RX 9070 XT has 16 GB of GDDR6, while the R9700 has 32 GB. It is these additional 16 GB, rather than an increase in GPU speed, that explain the professional positioning and the more than twofold difference in the recommended price.

Key Differences

Specification Radeon RX 9070 XT Radeon AI PRO R9700
Video Memory 16 GB GDDR6 32 GB GDDR6
Gaming Frequency 2400 MHz 2350 MHz
Boost Frequency up to 2970 MHz up to 2920 MHz
FP32 48.7 TFLOPS 47.8 TFLOPS
INT8 Matrix 389 TOPS 383 TOPS
Memory Bandwidth 640 GB/s 640 GB/s
Power Consumption 304 W 300 W
ECC No Yes in Linux
Form Factor Depends on Manufacturer Dual-slot
Recommended Price $599 $1299

Both cards feature a 256-bit bus, 64 MB of Infinity Cache, and a memory bandwidth of 640 GB/s. AMD did not increase the memory speed on the R9700, only doubled its capacity. The RX 9070 XT retains a slight edge in frequencies and theoretical computing power.

RX 9070 XT is Faster and More Cost-effective in Games

The Radeon AI PRO R9700 is not an enhanced gaming version of the RX 9070 XT. They have the same number of compute units, raster modules, and ray tracing accelerators, while the professional model has slightly lower frequencies.

The additional 16 GB of memory rarely increases frame rates. As long as the game, along with textures and other assets, fits within 16 GB, the extra memory on the R9700 is almost never utilized. The advantage of 32 GB may manifest in specific projects with heavy modifications, extreme texture packs, or professional visualization, but simply doubling the VRAM does not accelerate the GPU by itself.

For a gaming PC, the RX 9070 XT is noticeably more rational. It offers the same architecture, slightly higher frequencies, and significantly better performance per dollar spent. Partner versions also often come with massive cooling systems and increased power limits.

In contrast, the R9700 is designed for compact workstations. Its dual-slot design is more convenient when installing multiple graphics cards, but this advantage holds little significance for a typical gaming PC.

RX 9070 XT or R9700 for Local AI

In AI tasks, the balance of power shifts. Here, the R9700 excels not due to a more powerful GPU, but due to its ability to hold large models entirely in video memory.

According to AMD, certain popular configurations can require significantly more than 16 GB:

  • Stable Diffusion 3.5 Medium - around 17 GB;
  • Flux.1 Schnell - approximately 24 GB;
  • Mistral Small 3.1 24B Q8 - about 27 GB;
  • DeepSeek R1 Distill Qwen 32B Q6 - around 28 GB.

These projects fit within the 32 GB of the R9700 but exceed the capacity of the RX 9070 XT. On a 16-gigabyte card, one has to lower resolution, reduce context, heavily quantize the model, or offload some data to RAM. This can degrade results or significantly slow down performance.

If a model occupies 8-12 GB, the RX 9070 XT can achieve comparable or even slightly higher performance due to its increased frequencies. However, when consuming 20-30 GB, the advantage in frequencies becomes secondary: the R9700 retains the whole model in VRAM, whereas the RX 9070 XT has to compensate for the lack of memory.

ROCm Supports Both Graphics Cards

The RX 9070 XT is not limited to gaming. Both models support the ROCm computing platform and can be used with PyTorch, ONNX Runtime, and other machine learning tools.

Therefore, the gaming card is suitable for experiments, image generation, running compact language models, and as a home workstation. The R9700 is aimed at heavier projects where 16 GB becomes a hard limitation.

The professional model also offers:

  • 32 GB of video memory;
  • ECC in Linux;
  • Dual-slot form factor;
  • AMD Software: PRO Edition drivers;
  • More convenient layout for multi-GPU systems.

ECC does not affect gaming performance, but it can be useful during lengthy computations. The dual-slot format makes it easier to install two or more accelerators, while larger versions of the RX 9070 XT often take up three slots or more.

RX 9070 XT vs R9700: Which is Better to Buy

The Radeon RX 9070 XT is better suited for:

  • Gaming at 1440p and 4K;
  • A home computer with occasional AI tasks;
  • Rendering and editing, if 16 GB is sufficient;
  • Getting the maximum performance for the money spent.

The Radeon AI PRO R9700 should be chosen for:

  • Models that require more than 16 GB of VRAM;
  • Locally running large LLMs;
  • Heavy image generation;
  • Fine-tuning models;
  • Multi-GPU workstations;
  • Lengthy computations under Linux.

Conclusion

The RX 9070 XT and the Radeon AI PRO R9700 utilize virtually the same GPU. The gaming model is even slightly faster in terms of frequencies, so in regular games and tasks that fit within 16 GB of memory, the price premium for the R9700 does not provide a noticeable benefit.

The professional model becomes relevant once 16 GB becomes a real limitation. Its 32 GB of VRAM allow for running large models without constant data offloading to RAM, while the dual-slot form factor, ECC, and PRO drivers make it more convenient for multi-GPU workstations.

The RX 9070 XT is purchased for speed and price. The R9700 is for tasks that do not fit into 16 GB.

Advantages

  • Higher Boost Clock: 2920 MHz (2430 MHz vs 2920 MHz)
  • Larger Memory Size: 32GB (16GB vs 32GB)
  • Higher Bandwidth: 644.6GB/s (624.1GB/s vs 644.6GB/s)
  • Newer Launch Date: July 2025 (March 2025 vs July 2025)

Basic

AMD
Label Name
AMD
March 2025
Launch Date
July 2025
Desktop
Platform
Desktop
Radeon RX 9070 XT
Model Name
Radeon AI PRO R9700
Navi IV(RX 9000)
Generation
Radeon Pro Navi
1295 MHz
Base Clock
1660 MHz
2430 MHz
Boost Clock
2920 MHz
PCIe 4.0 x16
Bus Interface
PCIe 5.0 x16
Unknown
Transistors
53.9 billion
64
RT Cores
64
64
Compute Units
64
-
Tensor Cores
?
Tensor Cores are specialized processing units designed specifically for deep learning, providing higher training and inference performance compared to FP32 training. They enable rapid computations in areas such as computer vision, natural language processing, speech recognition, text-to-speech conversion, and personalized recommendations. The two most notable applications of Tensor Cores are DLSS (Deep Learning Super Sampling) and AI Denoiser for noise reduction.
128
256
TMUs
?
Texture Mapping Units (TMUs) serve as components of the GPU, which are capable of rotating, scaling, and distorting binary images, and then placing them as textures onto any plane of a given 3D model. This process is called texture mapping.
256
TSMC
Foundry
TSMC
4 nm
Process Size
4 nm
RDNA 4.0
Architecture
RDNA 4.0

Memory Specifications

16GB
Memory Size
32GB
GDDR6
Memory Type
GDDR6
256bit
Memory Bus
?
The memory bus width refers to the number of bits of data that the video memory can transfer within a single clock cycle. The larger the bus width, the greater the amount of data that can be transmitted instantaneously, making it one of the crucial parameters of video memory. The memory bandwidth is calculated as: Memory Bandwidth = Memory Frequency x Memory Bus Width / 8. Therefore, when the memory frequencies are similar, the memory bus width will determine the size of the memory bandwidth.
256bit
2438 MHz
Memory Clock
2518 MHz
624.1GB/s
Bandwidth
?
Memory bandwidth refers to the data transfer rate between the graphics chip and the video memory. It is measured in bytes per second, and the formula to calculate it is: memory bandwidth = working frequency × memory bus width / 8 bits.
644.6GB/s

Display and Media

1x HDMI 2.1a3x DisplayPort 2.1
Outputs
4x DisplayPort 2.1a

Theoretical Performance

233.3 GPixel/s
Pixel Rate
?
Pixel fill rate refers to the number of pixels a graphics processing unit (GPU) can render per second, measured in MPixels/s (million pixels per second) or GPixels/s (billion pixels per second). It is the most commonly used metric to evaluate the pixel processing performance of a graphics card.
373.8 GPixel/s
622.1 GTexel/s
Texture Rate
?
Texture fill rate refers to the number of texture map elements (texels) that a GPU can map to pixels in a single second.
747.5 GTexel/s
39.81 TFLOPS
FP16 (half)
?
An important metric for measuring GPU performance is floating-point computing capability. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable. Single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks, while double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy.
95.68 TFLOPS
622.1 GFLOPS
FP64 (double)
?
An important metric for measuring GPU performance is floating-point computing capability. Double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy, while single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable.
1495 GFLOPS
19.512 TFLOPS
FP32 (float)
?
An important metric for measuring GPU performance is floating-point computing capability. Single-precision floating-point numbers (32-bit) are used for common multimedia and graphics processing tasks, while double-precision floating-point numbers (64-bit) are required for scientific computing that demands a wide numeric range and high accuracy. Half-precision floating-point numbers (16-bit) are used for applications like machine learning, where lower precision is acceptable.
48.797 TFLOPS

Miscellaneous

4096
Shading Units
?
The most fundamental processing unit is the Streaming Processor (SP), where specific instructions and tasks are executed. GPUs perform parallel computing, which means multiple SPs work simultaneously to process tasks.
4096
128 KB per Array
L1 Cache
-
4 MB
L2 Cache
8 MB
220W
TDP
300W
1.3
Vulkan Version
?
Vulkan is a cross-platform graphics and compute API by Khronos Group, offering high performance and low CPU overhead. It lets developers control the GPU directly, reduces rendering overhead, and supports multi-threading and multi-core processors.
1.3
2.2
OpenCL Version
2.2
4.6
OpenGL
4.6
12 Ultimate (12_2)
DirectX
12 Ultimate (12_2)
2x 8-pin
Power Connectors
1x 16-pin
96
ROPs
?
The Raster Operations Pipeline (ROPs) is primarily responsible for handling lighting and reflection calculations in games, as well as managing effects like anti-aliasing (AA), high resolution, smoke, and fire. The more demanding the anti-aliasing and lighting effects in a game, the higher the performance requirements for the ROPs; otherwise, it may result in a sharp drop in frame rate.
128
6.8
Shader Model
6.8
550 W
Suggested PSU
700 W

Benchmarks

FP32 (float) / TFLOPS
Radeon RX 9070 XT
19.512
Radeon AI PRO R9700
48.797 +150%
3DMark Steel Nomad
Radeon RX 9070 XT
7238 +3%
Radeon AI PRO R9700
7014
Vulkan
Radeon RX 9070 XT
179584
Radeon AI PRO R9700
195059 +9%
OpenCL
Radeon RX 9070 XT
171744 +20%
Radeon AI PRO R9700
142792