Specifications Compared
| Spec | RTX-6000-ADA | V100 |
|---|---|---|
| TDP | 300W | 300W |
| VRAM | 48 GB | 16-32 GB |
| CUDA Cores | 18,176 | 5,120 |
| Memory Type | GDDR6 | HBM2 |
| Architecture | Ada Lovelace | Volta |
| Form Factors | PCIe | SXM2, PCIe |
| Interconnect | NVLink | NVLink, PCIe 3.0 |
| Tensor Cores | 568 | 640 |
| FP16 Performance | 91.1 TFLOPS | 125 TFLOPS |
| FP32 Performance | 91.1 TFLOPS | 15.7 TFLOPS |
| FP64 Performance | 1.4 TFLOPS | 7.8 TFLOPS |
| INT8 Performance | 1,457 TOPS | |
| Memory Bandwidth | 960 GB/s | 900 GB/s |
Performance Analysis
The RTX 6000 Ada excels in workloads requiring balanced precision: its FP32 performance matches FP16 at 91.1 TFLOPS, enabling efficient single-precision simulations and general compute tasks where the V100's 15.7 TFLOPS FP32 creates bottlenecks. For training large models with mixed precision, the V100's 125 TFLOPS FP16 provides a peak advantage, but real-world throughput often diminishes without matching FP32 support.
Memory capacity defines scalability: the RTX 6000 Ada's 48 GB GDDR6 versus the V100's 32 GB HBM2 allows larger batch sizes in deep learning, reducing overhead in LLM training or inference. Bandwidth differences are marginal at 960 GB/s for Ada versus 900 GB/s for V100, yet Ada's newer architecture sustains higher effective utilization. Inference benefits from Ada's PCIe form factor and balanced specs for diverse precisions, while V100 suits FP16-dominant pipelines optimized for Volta tensor cores.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
RTX 6000 Ada Generation
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA RTX 6000 Ada Generation 48GB VRAM | 48GB | 16 vCPU 188GB RAM | 🌍global | $0.50/GPU/hr | |||
RunPod | NVIDIA RTX 6000 Ada Generation 48GB VRAM | 48GB | 10 vCPU 167GB RAM | 🌍global | $0.77/GPU/hr | |||
 Massed Compute | NVIDIA RTX 6000 Ada Generation 48GB VRAM | 48GB | 12 vCPU 72GB RAM 350GB Storage | Iowa | $0.79/GPU/hr | Available | ||
Massed Compute | 2×NVIDIA RTX 6000 Ada Generation 48GB VRAM | 48GB | 26 vCPU 144GB RAM 700GB Storage | Iowa | $0.79/GPU/hr $1.58/hr total (2×) | Available | ||
Massed Compute | 4×NVIDIA RTX 6000 Ada Generation 48GB VRAM | 48GB | 52 vCPU 288GB RAM 1400GB Storage | Iowa | $0.79/GPU/hr $3.16/hr total (4×) | Available |
Tesla V100 32GB
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 TensorDock | NVIDIA Tesla V100 16GB 16GB VRAM | 16GB | 0 vCPU 0GB RAM | Texas | $0.19/GPU/hr | Available | ||
TensorDock | NVIDIA Tesla V100 16GB 16GB VRAM | 16GB | 0 vCPU 0GB RAM | New York City | $0.19/GPU/hr | Available | ||
TensorDock | NVIDIA Tesla V100 32GB 32GB VRAM | 32GB | 0 vCPU 0GB RAM | Texas | $0.29/GPU/hr | Available | ||
TensorDock | NVIDIA Tesla V100 32GB 32GB VRAM | 32GB | 0 vCPU 0GB RAM | New York City | $0.29/GPU/hr | Available | ||
 Lambda Labs | 8×NVIDIA Tesla V100 16GB 16GB VRAM | 16GB | 88 vCPU 448GB RAM 6041GB Storage | Texas | $0.79/GPU/hr $6.32/hr total (8×) | Available |
When to Choose the RTX 6000 Ada Generation
Opt for the RTX 6000 Ada in modern machine learning pipelines needing 48 GB VRAM for handling large models or datasets, such as fine-tuning transformers with batch sizes exceeding V100's 32 GB limit. Its 91.1 TFLOPS FP32 performance supports scientific simulations and graphics workloads where V100's 15.7 TFLOPS falls short. Lower entry pricing from $0.09 per hour makes it ideal for cost-sensitive scaling across 54 cloud offers.
When to Choose the Tesla V100 32GB
Select the V100 for legacy applications optimized for Volta tensor cores, leveraging its 125 TFLOPS FP16 for high-throughput inference in FP16-heavy models. It suits environments with existing codebases from 2017-era frameworks, where HBM2's 900 GB/s bandwidth maintains efficiency despite lower 32 GB capacity. Average pricing at $1.01 per hour across 46 offers provides value for short bursts without needing Ada's VRAM.
Use Cases
RTX 6000 Ada's 48 GB VRAM supports larger batch sizes for efficient training of large language models, unlike V100's 32 GB limit. Balanced 91.1 TFLOPS FP16/FP32 handles mixed-precision workflows better than V100's FP32 weakness.
The 48 GB capacity accommodates bigger models and concurrent requests during inference. Ada's 960 GB/s bandwidth and modern architecture yield higher sustained throughput than V100's 900 GB/s.
Fine-tuning benefits from 48 GB VRAM for parameter-efficient methods on large models. 91.1 TFLOPS FP32 aids precise updates where V100's 15.7 TFLOPS lags.
Image generation demands high VRAM for high-resolution outputs: 48 GB enables larger latents than V100's 32 GB. Balanced compute at 91.1 TFLOPS accelerates diffusion steps.
V100's 125 TFLOPS FP16 suits tensor-heavy simulations if optimized for Volta. RTX 6000 Ada's 91.1 TFLOPS FP32 and 48 GB VRAM favor general-purpose FP32 codes.
Frequently Asked Questions
Which GPU has more VRAM?▾
The RTX 6000 Ada provides 48 GB GDDR6 VRAM, surpassing the V100's 32 GB HBM2. This difference allows larger models and batch sizes in memory-intensive tasks. Cloud pricing starts at $0.09 per hour for Ada versus $0.29 per hour for V100.
How do FP32 performances compare?▾
RTX 6000 Ada delivers 91.1 TFLOPS FP32, far exceeding V100's 15.7 TFLOPS. This makes Ada preferable for FP32-dominant workloads like simulations. V100 compensates with 125 TFLOPS FP16 for tensor operations.
What are the memory bandwidth figures?▾
RTX 6000 Ada offers 960 GB/s with GDDR6, slightly above V100's 900 GB/s HBM2. Bandwidth impacts data transfer in training loops. Both support NVLink for multi-GPU scaling.
Which is cheaper in the cloud?▾
RTX 6000 Ada starts at $0.09 per hour (average $1.16 per hour across 54 offers), cheaper than V100's $0.29 per hour minimum (average $1.01 per hour across 46 offers). Entry-level pricing favors Ada for experimentation.
Do they have the same power consumption?▾
Both GPUs consume 300W TDP, ensuring similar thermal and power budgeting in clusters. RTX 6000 Ada uses PCIe form factor, while V100 supports SXM2 or PCIe. This parity aids direct swaps in compatible setups.
Which architecture is newer?▾
RTX 6000 Ada uses 2022 Ada Lovelace architecture, advancing beyond V100's 2017 Volta. Newer features include improved ray tracing and efficiency. FP16 performance is 91.1 TFLOPS on Ada versus 125 TFLOPS on V100.
Which is cheaper to rent, the RTX 6000 Ada or the V100?▾
Cloud rental prices for both the RTX 6000 Ada and V100 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 6000 Ada have compared to the V100?▾
The RTX 6000 Ada has 48 GB of GDDR6 memory. The V100 has 16 to 32 GB of HBM2 memory.
Can I find RTX 6000 Ada and V100 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 6000 Ada and the V100?▾
The RTX 6000 Ada uses the Ada Lovelace architecture (2022) while the V100 uses Volta (2017). The V100 delivers 1.4x the FP16 throughput and 1.1x the memory bandwidth of the RTX 6000 Ada.