Quadro GV100 vs Quadro RTX 3000
With 32GB on board versus 6GB for the Quadro RTX 3000, the Quadro GV100 carries more headroom for large models and memory-hungry workloads. Its memory bandwidth is 159% higher (870 GB/s vs 336 GB/s), translating directly to faster inference throughput. Price-wise, the Quadro RTX 3000 undercuts the Quadro GV100 by $2,317 GBP.
Maximum Capacity Reached. Remove a model to add another. (2/2)
Comparable or lower specs
Quadro GV100 vs Quadro RTX 3000: In-Depth Breakdown
VRAM: Quadro GV100 vs Quadro RTX 3000
With 32GB of VRAM against the Quadro RTX 3000's 6GB, the Quadro GV100 has a 26GB edge. VRAM is what determines whether a model fits without quantization at all — a 70B-parameter model in FP16 needs around 140GB, and smaller models still benefit from spare capacity. That extra headroom lets the Quadro GV100 load bigger models and run larger production batch sizes.
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 Quadro GV100 delivers 870 GB/s versus 336 GB/s on the Quadro RTX 3000, a 159% edge. For models already loaded into VRAM, token generation speed scales closely with this number: the Quadro GV100 will produce tokens proportionally faster in bandwidth-bound workloads.
AI Training & Compute
FP32 throughput is the metric that matters most for training, scientific simulation, and rendering work. The Quadro GV100 posts 14.8 TFLOPS versus 5.3 TFLOPS on the Quadro RTX 3000, a 179% compute lead. Expect training jobs and heavy matrix math to finish proportionally sooner on the Quadro GV100.
Price & Value
The Quadro RTX 3000 lists from $613 GBP, $2,317 GBP less than the Quadro GV100 at $2,930 GBP. For budget-constrained teams, the savings may outweigh the spec gap — especially if the smaller card covers your typical workload.
Which should you buy: Quadro GV100 or Quadro RTX 3000?
Go with the Quadro GV100 if you need maximum capacity: it's ahead on VRAM, bandwidth, and compute, so it's the stronger fit for large models and training jobs. The Quadro RTX 3000 is the cheaper pick ($2,317 GBP less) — worth it if your models already fit within its 6GB and you're not running heavy inference volume.
Frequently Asked Questions
Can the Quadro GV100 or Quadro RTX 3000 run large language models?
Which is faster for LLM inference, the Quadro GV100 or the Quadro RTX 3000?
Which is better for AI training?
Which should you buy: Quadro GV100 or Quadro RTX 3000?
Technical Specifications Comparison
Architecture & Cores
| Specification | Quadro GV100 | Quadro RTX 3000 |
|---|---|---|
| Architecture | Volta | Turing |
| CUDA Cores (CUDA Cores / CUDA Cores) | 5,120✓ | 1,920 |
Memory
| Specification | Quadro GV100 | Quadro RTX 3000 |
|---|---|---|
| VRAM Capacity | 32 GB✓ | 6 GB |
| Memory Type | HBM2 | GDDR6 |
| Memory Bus | 4096-bit✓ | 192-bit |
| Bandwidth | 870 GB/s✓ | 336 GB/s |
Connectivity & Power
| Specification | Quadro GV100 | Quadro RTX 3000 |
|---|---|---|
| Interface | PCIe 3.0 x16 | PCIe 3.0 x16 |
| TDP | 250 W | 160 W✓ |
| Released | Mar 2018 | Apr 2019 |
Workstation
| Specification | Quadro GV100 | Quadro RTX 3000 |
|---|---|---|
| FP32 (TFLOPS) | 14.8 TFLOPS✓ | 5.3 TFLOPS |
| ECC | Yes | Yes |
| NVLink | Yes✓ | No |
| Form factor | dual-slot | single-slot |