Specifications Compared
| Spec | RTX-5880-ADA | V100 |
|---|---|---|
| TDP | 285W | 300W |
| VRAM | 48 GB | 16-32 GB |
| CUDA Cores | 14,080 | 5,120 |
| Memory Type | GDDR6 | HBM2 |
| Architecture | Ada Lovelace | Volta |
| Form Factors | PCIe | SXM2, PCIe |
| Interconnect | NVLink, PCIe 3.0 | |
| Tensor Cores | 440 | 640 |
| FP16 Performance | 69.7 TFLOPS | 125 TFLOPS |
| FP32 Performance | 69.7 TFLOPS | 15.7 TFLOPS |
| INT8 Performance | 1,115 TOPS | |
| Memory Bandwidth | 960 GB/s | 900 GB/s |
Performance Analysis
FP16 performance favors V100 at 125 TFLOPS over RTX 5880 Ada's 69.7 TFLOPS: this benefits mixed-precision training where Volta tensor cores excel, enabling faster iterations on models fitting within 16 GB VRAM. Conversely, RTX 5880 Ada's matched 69.7 TFLOPS FP16 and FP32 supports FP32-dominant inference or simulations better than V100's 15.7 TFLOPS FP32, reducing precision conversion overhead.
Memory capacity defines workload feasibility: RTX 5880 Ada's 48 GB VRAM accommodates larger batch sizes or model parameters than V100's 16 GB, minimizing out-of-memory errors in large language models. Bandwidth edges to Ada at 960 GB/s from 900 GB/s, aiding data transfer in high-throughput inference. Overall, V100 suits FP16-heavy training on smaller datasets; Ada thrives in VRAM-constrained modern scenarios.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
Tesla V100 16GB
| 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 5880 Ada
RTX 5880 Ada excels in memory-bound tasks: its 48 GB GDDR6 VRAM handles models exceeding V100's 16 GB HBM2, ideal for inference on large language models or high-resolution Stable Diffusion. Balanced 69.7 TFLOPS FP32 outperforms V100's 15.7 TFLOPS for precision-sensitive computing.
The 285W TDP versus 300W enables more efficient power usage in dense PCIe deployments.
When to Choose the Tesla V100 16GB
V100 is optimal for cost-sensitive FP16 training: pricing starts at $0.10/hr with average $0.82/hr across 24 live offers, far below RTX 5880 Ada's unavailable status. Its 125 TFLOPS FP16 surpasses Ada's 69.7 TFLOPS for accelerated mixed-precision workloads.
NVLink and PCIe 3.0 interconnects support scalable multi-GPU setups unavailable on RTX 5880 Ada.
Use Cases
RTX 5880 Ada's 48 GB VRAM supports larger models and batch sizes than V100's 16 GB. Modern Ada architecture optimizes for current LLM scales despite V100's higher 125 TFLOPS FP16.
48 GB VRAM on RTX 5880 Ada fits massive models without quantization issues on V100's 16 GB. 69.7 TFLOPS FP32 matches inference demands better than V100's 15.7 TFLOPS.
RTX 5880 Ada's 48 GB capacity manages parameter-heavy fine-tuning beyond V100's 16 GB limit. Balanced FP16/FP32 at 69.7 TFLOPS aids efficient adaptation.
High VRAM of 48 GB on RTX 5880 Ada enables larger images and batches versus V100's 16 GB. 960 GB/s bandwidth accelerates generation workflows.
V100's 125 TFLOPS FP16 accelerates simulations faster than RTX 5880 Ada's 69.7 TFLOPS. Low $0.10/hr pricing suits extensive compute runs.
Frequently Asked Questions
What is the VRAM capacity of RTX 5880 Ada versus V100 16GB?▾
RTX 5880 Ada provides 48 GB GDDR6 VRAM, tripling V100's 16 GB HBM2. This allows larger models on Ada. Bandwidth reaches 960 GB/s on Ada from 900 GB/s on V100.
Which GPU has higher FP16 performance?▾
V100 achieves 125 TFLOPS FP16, exceeding RTX 5880 Ada's 69.7 TFLOPS. This suits training tasks. FP32 is 69.7 TFLOPS on Ada versus 15.7 TFLOPS on V100.
What are the power consumption differences?▾
RTX 5880 Ada has a 285W TDP, lower than V100's 300W. This favors denser Ada deployments. Efficiency aligns with Ada's modern 2024 architecture.
Is V100 available in the cloud and at what price?▾
V100 16GB offers start at $0.10/hr, averaging $0.82/hr across 24 providers. RTX 5880 Ada has no live offers. V100 supports SXM2 and PCIe form factors.
How do architectures compare?▾
RTX 5880 Ada uses 2024 Ada Lovelace for balanced compute at 69.7 TFLOPS FP16/FP32. V100's 2017 Volta excels in FP16 at 125 TFLOPS. Interconnects include NVLink on V100.
Which supports multi-GPU better?▾
V100 features NVLink and PCIe 3.0 for scaling. RTX 5880 Ada relies on PCIe alone. V100's options aid high-throughput clusters.
Which is cheaper to rent, the RTX 5880 Ada or the V100?▾
Cloud rental prices for both the RTX 5880 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 5880 Ada have compared to the V100?▾
The RTX 5880 Ada has 48 GB of GDDR6 memory. The V100 has 16 to 32 GB of HBM2 memory.
Can I find RTX 5880 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 5880 Ada and the V100?▾
The RTX 5880 Ada uses the Ada Lovelace architecture (2024) while the V100 uses Volta (2017). The V100 delivers 1.8x the FP16 throughput and 1.1x the memory bandwidth of the RTX 5880 Ada.