GPU Comparison
Select up to 2 GPUs to analyze their pricing, performance, and specifications side-by-side.
The Radeon PRO W5700 has more VRAM (8GB vs 6GB), making it better suited for large models and memory-intensive workloads. Its memory bandwidth is 33% higher (448 GB/s vs 336 GB/s), translating directly to faster inference throughput.
Maximum Capacity Reached. Remove a model to add another. (2/2)
Comparable or lower specs
Quadro RTX 3000 vs Radeon PRO W5700: In-Depth Breakdown
VRAM: Quadro RTX 3000 vs Radeon PRO W5700
The Radeon PRO W5700 carries 8GB of VRAM versus 6GB on the Quadro RTX 3000. VRAM capacity is the primary constraint for running AI models without quantization — a 70B-parameter model in FP16 requires roughly 140GB, and even smaller models benefit from extra headroom. The 2GB advantage here means the Radeon PRO W5700 can run larger models natively and handle bigger batch sizes in production.
Inference Speed: Memory Bandwidth
Memory bandwidth determines how quickly data is fed to the compute units — it's the main bottleneck for autoregressive inference (token generation in LLMs). The Radeon PRO W5700 delivers 448 GB/s versus 336 GB/s on the Quadro RTX 3000, a 33% edge. For models already loaded into VRAM, token generation speed scales closely with this number: the Radeon PRO W5700 will produce tokens proportionally faster in bandwidth-bound workloads.
AI Training & Compute
For model training, scientific simulation, and rendering, FP32 throughput is the key metric. The Radeon PRO W5700 delivers 8.5 TFLOPS against 5.3 TFLOPS for the Quadro RTX 3000 — a 60% compute advantage. Training runs and heavy matrix operations will complete proportionally faster on the Radeon PRO W5700.
Which should you buy: Quadro RTX 3000 or Radeon PRO W5700?
The Radeon PRO W5700 is the stronger choice for large-model workloads where VRAM is the bottleneck. The Quadro RTX 3000 is more economical, and sufficient if your models fit within its 6GB.
Frequently Asked Questions
Can the Quadro RTX 3000 or Radeon PRO W5700 run large language models?
Which is faster for LLM inference, the Quadro RTX 3000 or the Radeon PRO W5700?
Which is better for AI training?
Technical Specifications Comparison
Architecture & Cores
| Specification | Quadro RTX 3000 | Radeon PRO W5700 |
|---|---|---|
| Architecture | Turing | RDNA 1 |
| CUDA Cores (CUDA Cores / Stream Processors) | 1,920 | 2,304✓ |
Memory
| Specification | Quadro RTX 3000 | Radeon PRO W5700 |
|---|---|---|
| VRAM Capacity | 6 GB | 8 GB✓ |
| Memory Type | GDDR6 | GDDR6 |
| Memory Bus | 192-bit | 256-bit✓ |
| Bandwidth | 336 GB/s | 448 GB/s✓ |
Connectivity & Power
| Specification | Quadro RTX 3000 | Radeon PRO W5700 |
|---|---|---|
| Interface | PCIe 3.0 x16 | PCIe 4.0 x16 |
| TDP | 160 W | 130 W✓ |
| Released | Apr 2019 | Dec 2019 |
Workstation
| Specification | Quadro RTX 3000 | Radeon PRO W5700 |
|---|---|---|
| FP32 (TFLOPS) | 5.3 TFLOPS | 8.5 TFLOPS✓ |
| ECC | Yes | Yes |
| NVLink | No | No |
| Form factor | single-slot | dual-slot |