Specifications Compared
| Spec | RTX-4000-ADA | TITAN-V |
|---|---|---|
| TDP | 130W | 250W |
| VRAM | 20 GB | 12 GB |
| CUDA Cores | 6,144 | 5,120 |
| Memory Type | GDDR6 | HBM2 |
| Architecture | Ada Lovelace | Volta |
| Form Factors | PCIe | PCIe |
| Interconnect | ||
| Tensor Cores | 192 | 640 |
| FP16 Performance | 26.7 TFLOPS | 13.8 TFLOPS |
| FP32 Performance | 26.7 TFLOPS | 13.8 TFLOPS |
| INT8 Performance | 427 TOPS | |
| Memory Bandwidth | 360 GB/s | 653 GB/s |
Performance Analysis
Compute performance favors the RTX 4000 Ada decisively: its 26.7 TFLOPS in FP16 and FP32 nearly doubles the TITAN V's 13.8 TFLOPS in both precisions. For deep learning training, this delta translates to approximately twice the throughput on tensor operations, reducing epoch times significantly. Inference workloads similarly benefit, as higher FP16 performance accelerates batched predictions without precision loss.
Memory specifications present a mixed picture. The RTX 4000 Ada's 20 GB GDDR6 VRAM exceeds the TITAN V's 12 GB HBM2, enabling larger models or batch sizes before out-of-memory errors occur. However, TITAN V's 653 GB/s bandwidth surpasses the Ada's 360 GB/s, aiding memory-bound tasks like large-scale simulations where data transfer rates limit speed.
Power efficiency underscores the Ada's edge: 130W TDP versus 250W allows more GPUs per server, lowering operational costs in cloud environments.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
RTX 4000 Ada
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA RTX 4000 Ada Generation 20GB VRAM | 20GB | 8 vCPU 50GB RAM | 🌍global | $0.26/GPU/hr | |||
 Vast.ai | NVIDIA RTX 4000 Ada Generation 20GB VRAM | 20GB | 64 vCPU 42GB RAM 505GB Storage | Hungary | $0.40/GPU/hr | Available | ||
RunPod | NVIDIA RTX 4000 Ada Generation 20GB VRAM | 20GB | 8 vCPU 50GB RAM | 🌍global | $0.44/GPU/hr | |||
RunPod | NVIDIA RTX 4000 Ada Generation 20GB VRAM | 20GB | 0 vCPU 0GB RAM | 🌍global | $0.57/GPU/hr |
When to Choose the RTX 4000 Ada
The RTX 4000 Ada excels in contemporary AI pipelines demanding high VRAM and compute density. Its 20 GB capacity supports training models up to 13 billion parameters without multi-GPU setups, unlike the TITAN V's 12 GB limit. Availability at $0.09 per hour average $0.22 per hour across nine providers ensures scalable deployments.
Power-sensitive applications benefit from its 130W TDP, fitting edge or dense cloud instances efficiently.
When to Choose the TITAN V
The TITAN V suits niche workloads optimized for Volta-specific features or requiring peak memory bandwidth. Its 653 GB/s throughput outperforms the RTX 4000 Ada's 360 GB/s in bandwidth-saturated tasks like certain HPC simulations. Legacy software stacks tied to 2017-era drivers may necessitate this GPU despite its age.
Use Cases
RTX 4000 Ada's 20 GB VRAM and 26.7 TFLOPS FP16 handle larger language models than TITAN V's 12 GB and 13.8 TFLOPS. This reduces multi-GPU needs for training billion-parameter models.
The 26.7 TFLOPS FP16 performance doubles TITAN V's 13.8 TFLOPS, enabling higher throughput for real-time queries. 20 GB VRAM supports bigger batch sizes without truncation.
RTX 4000 Ada's doubled FP32 at 26.7 TFLOPS accelerates gradient computations over TITAN V's 13.8 TFLOPS. Extra 8 GB VRAM fits full datasets during adaptation.
20 GB VRAM loads high-resolution diffusion models entirely, unlike TITAN V's 12 GB constraint. 26.7 TFLOPS FP16 speeds up iterative sampling by nearly double.
TITAN V's 653 GB/s bandwidth excels in memory-intensive simulations over RTX 4000 Ada's 360 GB/s. HBM2 reduces bottlenecks in large matrix operations.
Frequently Asked Questions
Which GPU has more VRAM: RTX 4000 Ada or TITAN V?▾
The RTX 4000 Ada provides 20 GB GDDR6 VRAM, exceeding the TITAN V's 12 GB HBM2. This allows larger models in AI tasks. Extra capacity prevents swapping in memory-constrained workloads.
How do FP32 performance levels compare between RTX 4000 Ada and TITAN V?▾
RTX 4000 Ada delivers 26.7 TFLOPS FP32, while TITAN V offers 13.8 TFLOPS. The Ada processes general-purpose compute twice as fast. This impacts scientific and rendering applications directly.
What is the memory bandwidth difference?▾
TITAN V achieves 653 GB/s with HBM2, surpassing RTX 4000 Ada's 360 GB/s GDDR6. Higher bandwidth aids data-heavy transfers. Ada's VRAM volume compensates in many scenarios.
Which GPU is more power efficient?▾
RTX 4000 Ada consumes 130W TDP versus TITAN V's 250W. Lower power enables denser cloud packing. This reduces costs in prolonged runs.
Is TITAN V available on cloud GPU providers?▾
TITAN V has no live cloud offers currently. RTX 4000 Ada starts at $0.09 per hour, averaging $0.22 per hour across nine providers. Availability favors the newer GPU.
RTX 4000 Ada vs TITAN V: which is newer?▾
RTX 4000 Ada uses 2023 Ada Lovelace architecture, while TITAN V dates to 2017 Volta. Six-year gap brings compute and efficiency gains. Newer design supports current software stacks.
Which is cheaper to rent, the RTX 4000 Ada or the TITAN V?▾
Cloud rental prices for both the RTX 4000 Ada 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 4000 Ada have compared to the TITAN V?▾
The RTX 4000 Ada has 20 GB of GDDR6 memory. The TITAN V has 12 GB of HBM2 memory.
Can I find RTX 4000 Ada 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 4000 Ada and the TITAN V?▾
The RTX 4000 Ada uses the Ada Lovelace architecture (2023) while the TITAN V uses Volta (2017). The RTX 4000 Ada delivers 1.9x the FP16 throughput and 1.8x the memory bandwidth of the TITAN V.