Quadro GV100 vs Quadro RTX 4000
The Quadro GV100 has more VRAM (32GB vs 8GB), making it better suited for large models and memory-intensive workloads. Memory bandwidth runs 109% ahead (870 GB/s versus 416 GB/s), which feeds straight through into quicker inference. The Quadro RTX 4000 is $10,688 EUR cheaper than the Quadro GV100.
Maximum Capacity Reached. Remove a model to add another. (2/2)
Comparable or lower specs
Quadro GV100 vs Quadro RTX 4000: In-Depth Breakdown
VRAM: Quadro GV100 vs Quadro RTX 4000
The Quadro GV100 carries 32GB of VRAM versus 8GB on the Quadro RTX 4000. 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 24GB advantage here means the Quadro GV100 can run larger models natively and handle bigger batch sizes in production.
Inference Speed: Memory Bandwidth
The rate data moves to the compute units — memory bandwidth — is what caps autoregressive inference speed (token generation in LLMs). Here the Quadro GV100 reaches 870 GB/s against 416 GB/s for the Quadro RTX 4000, a 109% advantage. Once a model is resident in VRAM, token throughput tracks this figure closely, so the Quadro GV100 generates tokens proportionally faster on bandwidth-bound workloads.
AI Training & Compute
For model training, scientific simulation, and rendering, FP32 throughput is the key metric. The Quadro GV100 delivers 14.8 TFLOPS against 7.1 TFLOPS for the Quadro RTX 4000 — a 108% compute advantage. Training runs and heavy matrix operations will complete proportionally faster on the Quadro GV100.
Price & Value
Pricing starts at $549 EUR for the Quadro RTX 4000, a $10,688 EUR saving over the Quadro GV100's $11,237 EUR. Teams working within a tighter budget may find that saving worth more than the spec gap, particularly if the smaller card already covers their typical workload.
Which should you buy: Quadro GV100 or Quadro RTX 4000?
Choose the Quadro GV100 for maximum capacity — it leads on VRAM, bandwidth, and compute, making it the better fit for large models and training jobs. The Quadro RTX 4000 is the more budget-friendly option ($10,688 EUR less) — a solid choice if your models fit within its 8GB and inference volume is moderate.
Frequently Asked Questions
Can the Quadro GV100 or Quadro RTX 4000 run large language models?
Which is faster for LLM inference, the Quadro GV100 or the Quadro RTX 4000?
Which is better for AI training?
Which should you buy: Quadro GV100 or Quadro RTX 4000?
Technical Specifications Comparison
Architecture & Cores
| Specification | Quadro GV100 | Quadro RTX 4000 |
|---|---|---|
| Architecture | Volta | Turing |
| CUDA Cores (CUDA Cores / CUDA Cores) | 5,120✓ | 2,304 |
Memory
| Specification | Quadro GV100 | Quadro RTX 4000 |
|---|---|---|
| VRAM Capacity | 32 GB✓ | 8 GB |
| Memory Type | HBM2 | GDDR6 |
| Memory Bus | 4096-bit✓ | 256-bit |
| Bandwidth | 870 GB/s✓ | 416 GB/s |
Connectivity & Power
| Specification | Quadro GV100 | Quadro RTX 4000 |
|---|---|---|
| Interface | PCIe 3.0 x16 | PCIe 3.0 x16 |
| TDP | 250 W | 160 W✓ |
| Released | Mar 2018 | Oct 2018 |
Workstation
| Specification | Quadro GV100 | Quadro RTX 4000 |
|---|---|---|
| FP32 (TFLOPS) | 14.8 TFLOPS✓ | 7.1 TFLOPS |
| ECC | Yes | Yes |
| NVLink | Yes✓ | No |
| Form factor | dual-slot | single-slot |