Radeon AI Pro R9700
A workstation-class AI acceleration GPU introduced by AMD, based on the RDNA 4 architecture. It features 32 GB of video memory and 640 GB/s memory bandwidth, targeting local AI inference and professional compute workloads.
Timeline (last 90 days)
The AMD Radeon AI Pro R9700 and Intel Arc Pro B70 both feature 32GB of VRAM and a 256-bit memory bus width, with memory bandwidth differing by less than 5%.
The R9700 launched at $1,299 and the B70 launched at $949.
As of September price tracking, the R9700 falls in the $1,700–$1,810 range and the B70 falls in the $1,300–$1,460 range.
Calculated by VRAM capacity, the B70 is approximately $41/GB and the R9700 is approximately $55/GB.
The R9700 is based on the RDNA4 architecture, featuring 64 compute units, 4,096 stream processors, 128 AI accelerators, 640 GB/s bandwidth, 47.8 TFLOPS FP32 compute, and 191 TFLOPS dense FP16 matrix throughput.
Puget Systems measurements show the R9700's FP32 is approximately twice that of the B70, and its matrix throughput is approximately 5 times higher.
In a llama.cpp environment with Qwen3 27B, the R9700 achieved 27.1 tokens/s (approximately 65% of bandwidth ceiling) and the B70 achieved 21.4 tokens/s (just over approximately 50%).
When enabling multi-token prediction (MTP) with a draft depth of 2, the R9700 rose from 27.1 to 46.2 tokens/s (+70%) and the B70 rose from 21.4 to 28.4 tokens/s (+33%).
The MESA 26.1 driver doubled the B70's Vulkan path performance on MoE-type models like Qwen3 30B-A3B from 38 to 76 tokens/s, approaching the R9700's approximately 77 tokens/s.
On dense mid-scale models (such as 27B), the AMD R9700 leads significantly; on MoE models the two are roughly on par; and on small workloads the B70 has a slight edge.
All Facts (8)
The AMD Radeon AI Pro R9700 and Intel Arc Pro B70 both feature 32GB of VRAM and a 256-bit memory bus width, with memory bandwidth differing by less than 5%.
50%UnverifiedThe R9700 launched at $1,299 and the B70 launched at $949.
50%UnverifiedThe R9700 is based on the RDNA4 architecture, featuring 64 compute units, 4,096 stream processors, 128 AI accelerators, 640 GB/s bandwidth, 47.8 TFLOPS FP32 compute, and 191 TFLOPS dense FP16 matrix throughput.
50%UnverifiedPuget Systems measurements show the R9700's FP32 is approximately twice that of the B70, and its matrix throughput is approximately 5 times higher.
50%UnverifiedIn a llama.cpp environment with Qwen3 27B, the R9700 achieved 27.1 tokens/s (approximately 65% of bandwidth ceiling) and the B70 achieved 21.4 tokens/s (just over approximately 50%).
50%UnverifiedWhen enabling multi-token prediction (MTP) with a draft depth of 2, the R9700 rose from 27.1 to 46.2 tokens/s (+70%) and the B70 rose from 21.4 to 28.4 tokens/s (+33%).
50%UnverifiedThe MESA 26.1 driver doubled the B70's Vulkan path performance on MoE-type models like Qwen3 30B-A3B from 38 to 76 tokens/s, approaching the R9700's approximately 77 tokens/s.
50%UnverifiedOn dense mid-scale models (such as 27B), the AMD R9700 leads significantly; on MoE models the two are roughly on par; and on small workloads the B70 has a slight edge.
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