Specifications Compared
| Spec | RTX-PRO-6000-BLACKWELL | TITAN-V |
|---|---|---|
| TDP | 400W | 250W |
| VRAM | 96 GB | 12 GB |
| CUDA Cores | 21,760 | 5,120 |
| Memory Type | GDDR7 | HBM2 |
| Architecture | Blackwell | Volta |
| Form Factors | PCIe | PCIe |
| Interconnect | NVLink | |
| Tensor Cores | 680 | 640 |
| FP8 Performance | 2,000 TFLOPS | |
| FP16 Performance | 125 TFLOPS | 13.8 TFLOPS |
| FP32 Performance | 125 TFLOPS | 13.8 TFLOPS |
| INT8 Performance | 2,000 TOPS | |
| Memory Bandwidth | 1,792 GB/s | 653 GB/s |
Performance Analysis
Compute throughput defines a clear winner in AI tasks: the RTX PRO 6000 achieves 125 TFLOPS in FP16 and FP32, approximately nine times the TITAN V's 13.8 TFLOPS in both. This delta translates to dramatically faster model training and inference; training a large language model on the RTX PRO 6000 completes in roughly one-ninth the time of the TITAN V, assuming memory constraints allow.
Memory capacity and bandwidth profoundly impact real-world usability. With 96 GB GDDR7 versus 12 GB HBM2, the RTX PRO 6000 handles massive models or large batch sizes without swapping to system RAM, which cripples performance on the TITAN V for datasets exceeding 12 GB. The 1792 GB/s bandwidth, nearly three times the TITAN V's 653 GB/s, sustains high throughput during memory-intensive operations like gradient accumulation in training or token generation in inference.
Power efficiency per TFLOP favors the TITAN V slightly at lower absolute power draw of 250 W, but the RTX PRO 6000's 400 W TDP enables scaling to multi-GPU setups via NVLink. For inference at FP8, the RTX PRO 6000's 2000 TFLOPS provides unmatched speed for quantized models, irrelevant on the TITAN V.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
RTX PRO 6000
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 VERDA | 2×NVIDIA RTX PRO 6000 Blackwell 96GB VRAM | 96GB | 60 vCPU 180GB RAM | Helsinki | $1.89/GPU/hr $3.78/hr total (2×) | Available | ||
VERDA | NVIDIA RTX PRO 6000 Blackwell 96GB VRAM | 96GB | 30 vCPU 90GB RAM | Helsinki | $1.89/GPU/hr | Available |
When to Choose the RTX PRO 6000
The RTX PRO 6000 excels in modern machine learning pipelines requiring vast memory. Deploy it for training large language models with billions of parameters, where 96 GB VRAM accommodates full model states and large batches, unlike the TITAN V's 12 GB limit. Cloud availability at $0.59 per hour minimum pricing suits scalable, on-demand workloads.
Inference for production-scale generative AI favors the RTX PRO 6000 due to 2000 TFLOPS FP8 performance and 1792 GB/s bandwidth, enabling high-throughput serving of quantized models.
When to Choose the TITAN V
The TITAN V suits legacy applications or budget-constrained local setups where existing hardware depreciates slowly. Its 250 W TDP consumes less power than the RTX PRO 6000's 400 W, ideal for small-scale scientific simulations fitting within 12 GB HBM2 and 653 GB/s bandwidth.
Choose the TITAN V for prototyping simple neural networks or Volta-specific codebases, avoiding cloud costs since no live offers exist.
Use Cases
The RTX PRO 6000's 96 GB VRAM and 125 TFLOPS FP16 handle large models and batches, while the TITAN V's 12 GB limits scale severely.
2000 TFLOPS FP8 and 1792 GB/s bandwidth on the RTX PRO 6000 enable high-throughput quantized inference; TITAN V lacks FP8 support.
125 TFLOPS FP32 and ample 96 GB memory support efficient fine-tuning of large models on RTX PRO 6000, exceeding TITAN V capabilities.
RTX PRO 6000's superior bandwidth and VRAM accelerate diffusion model generation at scale; TITAN V struggles with memory for high-res images.
Small simulations fit TITAN V's 12 GB HBM2; larger HPC tasks demand RTX PRO 6000's 96 GB and NVLink.
Frequently Asked Questions
What is the VRAM difference between RTX PRO 6000 and TITAN V?▾
The RTX PRO 6000 offers 96 GB GDDR7 VRAM, eight times the TITAN V's 12 GB HBM2. This enables handling much larger models on the newer GPU. Bandwidth reaches 1792 GB/s on RTX PRO 6000 versus 653 GB/s on TITAN V.
How do FP16 performance figures compare?▾
RTX PRO 6000 delivers 125 TFLOPS FP16, over nine times the TITAN V's 13.8 TFLOPS. This gap accelerates tensor operations in AI training. FP32 matches at 125 TFLOPS versus 13.8 TFLOPS.
Is TITAN V available in the cloud?▾
No live cloud offers exist for TITAN V. RTX PRO 6000 pricing starts at $0.59 per hour, averaging $1.25 per hour across five providers. TITAN V suits on-premises use only.
What are the power requirements?▾
RTX PRO 6000 has a 400 W TDP, higher than TITAN V's 250 W. This reflects greater compute density in Blackwell architecture. Both use PCIe form factor.
Does RTX PRO 6000 support FP8?▾
RTX PRO 6000 provides 2000 TFLOPS FP8 for efficient inference. TITAN V lacks FP8 capability. This boosts quantized model performance significantly.
Which has NVLink interconnect?▾
RTX PRO 6000 includes NVLink for multi-GPU scaling. TITAN V has no listed interconnect. NVLink enhances distributed training efficiency.
Which is cheaper to rent, the RTX PRO 6000 or the TITAN V?▾
Cloud rental prices for both the RTX PRO 6000 and TITAN V vary by provider, configuration, and availability. This page shows live pricing from 25+ providers updated every 60 seconds. Scroll to the Live Cloud Pricing section to compare current rates.
How much VRAM does the RTX PRO 6000 have compared to the TITAN V?▾
The RTX PRO 6000 has 96 GB of GDDR7 memory. The TITAN V has 12 GB of HBM2 memory.
Can I find RTX PRO 6000 and TITAN V GPUs available to rent right now?▾
Yes. This page shows real-time availability across 25+ cloud GPU providers. The Live Cloud Pricing section displays only in-stock offers with current pricing.
What is the main difference between the RTX PRO 6000 and the TITAN V?▾
The RTX PRO 6000 uses the Blackwell architecture (2025) while the TITAN V uses Volta (2017). The RTX PRO 6000 delivers 9.1x the FP16 throughput and 2.7x the memory bandwidth of the TITAN V.