Specifications Compared
| Spec | RTX-4080 | RTX-6000-ADA |
|---|---|---|
| TDP | 320W | 300W |
| VRAM | 16 GB | 48 GB |
| CUDA Cores | 9,728 | 18,176 |
| Memory Type | GDDR6X | GDDR6 |
| Architecture | Ada Lovelace | Ada Lovelace |
| Form Factors | PCIe | PCIe |
| Interconnect | NVLink | |
| Tensor Cores | 304 | 568 |
| FP16 Performance | 48.7 TFLOPS | 91.1 TFLOPS |
| FP32 Performance | 48.7 TFLOPS | 91.1 TFLOPS |
| INT8 Performance | 780 TOPS | 1,457 TOPS |
| Memory Bandwidth | 717 GB/s | 960 GB/s |
Performance Analysis
The RTX 6000 Ada outperforms the RTX 4080 SUPER in raw compute with 91.1 TFLOPS FP16 and FP32 versus 48.7 TFLOPS, doubling throughput for training deep learning models where half-precision dominates. This delta accelerates LLM training iterations by handling larger models or batches faster. Inference benefits similarly, as higher TFLOPS reduce latency for real-time deployments. Memory specs define practical limits: 48 GB VRAM on the RTX 6000 Ada supports batch sizes up to three times larger than the RTX 4080 SUPER's 16 GB, preventing out-of-memory errors in fine-tuning or Stable Diffusion with high-resolution images. The 960 GB/s bandwidth versus 717 GB/s sustains data flow for these operations, minimizing bottlenecks in scientific computing simulations. Despite a 300W TDP compared to 320W, the RTX 6000 Ada's efficiency shines in sustained professional loads.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
RTX 4080 SUPER
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA GeForce RTX 4080 SUPER 16GB VRAM | 16GB | 6 vCPU 35GB RAM | 🌍global | $0.50/GPU/hr | |||
RunPod | NVIDIA GeForce RTX 4080 16GB VRAM | 16GB | 6 vCPU 35GB RAM | 🌍global | $0.50/GPU/hr |
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 |
When to Choose the RTX 4080 SUPER
The RTX 4080 SUPER suits cost-sensitive users for lighter AI inference or gaming-integrated workflows. At an average $0.32 per hour versus $1.23 per hour, it delivers 48.7 TFLOPS FP16 for Stable Diffusion or small LLM inference without NVLink needs. Its 16 GB GDDR6X handles batch sizes fitting consumer-scale projects efficiently.
When to Choose the RTX 6000 Ada Generation
Opt for the RTX 6000 Ada in memory-bound professional tasks like large LLM training or fine-tuning. The 48 GB VRAM and 960 GB/s bandwidth enable massive datasets, while 91.1 TFLOPS FP16 outperforms the RTX 4080 SUPER by 87 percent. NVLink supports multi-GPU clusters unavailable on the PCIe RTX 4080 SUPER.
Use Cases
The RTX 6000 Ada's 48 GB VRAM and 91.1 TFLOPS FP16 support larger models and batches than the RTX 4080 SUPER's 16 GB and 48.7 TFLOPS.
Higher 960 GB/s bandwidth and 48 GB capacity on the RTX 6000 Ada reduce latency for production-scale inference versus the RTX 4080 SUPER.
RTX 6000 Ada's NVLink and 91.1 TFLOPS enable efficient multi-GPU fine-tuning of large models, exceeding the PCIe-limited RTX 4080 SUPER.
RTX 4080 SUPER's 16 GB GDDR6X suffices for high-resolution image generation at lower $0.32 per hour cost, matching needs without excess VRAM.
The RTX 6000 Ada's 48 GB VRAM and 960 GB/s bandwidth manage complex simulations better than the RTX 4080 SUPER's 16 GB.
Frequently Asked Questions
Which has more VRAM: RTX 4080 SUPER or RTX 6000 Ada?▾
The RTX 6000 Ada provides 48 GB GDDR6 VRAM, triple the RTX 4080 SUPER's 16 GB GDDR6X. This favors the RTX 6000 Ada for large-model AI tasks.
What are the FP32 performance differences?▾
RTX 6000 Ada delivers 91.1 TFLOPS FP32, 87 percent higher than RTX 4080 SUPER's 48.7 TFLOPS. Both share Ada Lovelace architecture for comparable efficiency.
How do cloud prices compare?▾
RTX 4080 SUPER starts at $0.17 per hour average $0.32 per hour across 3 offers; RTX 6000 Ada at $0.20 per hour average $1.23 per hour across 54 offers.
Does RTX 6000 Ada support NVLink?▾
Yes, RTX 6000 Ada includes NVLink for multi-GPU connectivity, unlike the PCIe-only RTX 4080 SUPER. This boosts scaling in training workloads.
Which has higher memory bandwidth?▾
RTX 6000 Ada offers 960 GB/s, 34 percent above RTX 4080 SUPER's 717 GB/s. Higher bandwidth aids data-heavy inference and simulations.
What are the TDPs?▾
RTX 4080 SUPER consumes 320W; RTX 6000 Ada uses 300W. Both fit PCIe form factors for standard cloud deployments.
Which is cheaper to rent, the RTX 4080 or the RTX 6000 Ada?▾
Cloud rental prices for both the RTX 4080 and RTX 6000 Ada 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 4080 have compared to the RTX 6000 Ada?▾
The RTX 4080 has 16 GB of GDDR6X memory. The RTX 6000 Ada has 48 GB of GDDR6 memory.
Can I find RTX 4080 and RTX 6000 Ada 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 4080 and the RTX 6000 Ada?▾
The RTX 4080 uses the Ada Lovelace architecture (2022) while the RTX 6000 Ada uses Ada Lovelace (2022). The RTX 6000 Ada delivers 1.9x the FP16 throughput and 1.3x the memory bandwidth of the RTX 4080.