Specifications Compared
| Spec | RTX-3080 | RTX-A4000 |
|---|---|---|
| TDP | 320W | 140W |
| VRAM | 10-12 GB | 16 GB |
| CUDA Cores | 8,704 | 6,144 |
| Memory Type | GDDR6X | GDDR6 |
| Architecture | Ampere | Ampere |
| Form Factors | PCIe | PCIe |
| Interconnect | ||
| Tensor Cores | 272 | 192 |
| FP16 Performance | 29.8 TFLOPS | 19.2 TFLOPS |
| FP32 Performance | 29.8 TFLOPS | 19.2 TFLOPS |
| Memory Bandwidth | 760 GB/s | 448 GB/s |
Performance Analysis
RTX 3080 holds a compute edge: 29.8 TFLOPS FP16 and FP32 versus A4500's 19.2 TFLOPS, a 55 percent advantage. This translates to faster deep learning training and inference, as FP16 enables high-speed mixed-precision workflows without FP32 fallback penalties on either GPU.
Memory bandwidth impacts batch sizes directly: RTX 3080's 760 GB/s supports larger batches in memory-bound training compared to A4500's 448 GB/s. Real-world throughput rises for data-heavy tasks like image processing on RTX 3080, though A4500's 16 GB VRAM accommodates models exceeding RTX 3080's 10-12 GB limit.
Power draw varies significantly: 320W TDP on RTX 3080 demands robust cooling, while A4500's 140W enables denser cloud deployments. Overall, RTX 3080 prioritizes speed, A4500 balances capacity and efficiency.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
RTX A4500
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 TensorDock | NVIDIA RTX A4000 16GB VRAM | 16GB | 0 vCPU 0GB RAM | Tallinn, Harjumaa | $0.08/GPU/hr | Available | ||
 Vast.ai | 8×NVIDIA RTX A4000 16GB VRAM | 16GB | 80 vCPU 201GB RAM 1698GB Storage | United Kingdom | $0.15/GPU/hr $1.17/hr total (8×) | Available | ||
 Hyperstack | 4×NVIDIA RTX A4000 16GB VRAM | 16GB | 16 vCPU 86GB RAM 500GB Storage | Norway | $0.15/GPU/hr $0.60/hr total (4×) | Available | ||
Hyperstack | 2×NVIDIA RTX A4000 16GB VRAM | 16GB | 8 vCPU 43GB RAM 200GB Storage | Norway | $0.15/GPU/hr $0.30/hr total (2×) | Available | ||
Hyperstack | NVIDIA RTX A4000 16GB VRAM | 16GB | 4 vCPU 21GB RAM 100GB Storage | Norway | $0.15/GPU/hr | Available |
When to Choose the RTX 3080
Select RTX 3080 for compute-intensive workloads fitting within 10-12 GB VRAM. Its 29.8 TFLOPS and 760 GB/s bandwidth accelerate Stable Diffusion or mid-sized model inference, where A4500 trails at 19.2 TFLOPS and 448 GB/s. Lower cloud pricing from $0.06/hr (average $0.13/hr) enhances value for high-volume tasks.
Budget-sensitive users benefit most: 55 percent higher performance at half the A4500's average hourly cost suits extended training runs.
When to Choose the RTX A4500
RTX A4500 suits memory-constrained scenarios requiring over 12 GB VRAM. Its 16 GB capacity handles large LLMs or datasets that cause out-of-memory errors on RTX 3080's 10-12 GB. Lower 140W TDP fits power-limited instances better than 320W.
Professional pipelines with certified drivers favor A4500, despite reduced 19.2 TFLOPS throughput.
Use Cases
LLM training demands high VRAM for parameter-heavy models; A4500's 16 GB exceeds RTX 3080's 10-12 GB to avoid swapping. Bandwidth of 448 GB/s suffices for stable large-batch training.
Inference batches fit 10-12 GB easily; RTX 3080's 29.8 TFLOPS and 760 GB/s yield 55 percent faster latencies than A4500's 19.2 TFLOPS.
Mid-sized models fit both VRAM capacities; RTX 3080 offers speed at 29.8 TFLOPS, A4500 provides 16 GB for edge cases, select by cost or power.
Image generation leverages high bandwidth: 760 GB/s on RTX 3080 speeds pipelines over A4500's 448 GB/s. 10-12 GB VRAM handles typical workflows.
FP32 simulations benefit from 29.8 TFLOPS on RTX 3080 versus 19.2 TFLOPS on A4500. Bandwidth edge accelerates data movement in HPC codes.
Frequently Asked Questions
Which GPU has more VRAM: RTX 3080 or RTX A4500?▾
RTX A4500 provides 16 GB GDDR6 VRAM, surpassing RTX 3080's 10-12 GB GDDR6X. This advantage aids large-model loading in training or inference.
What are the TFLOPS ratings for these GPUs?▾
RTX 3080 delivers 29.8 TFLOPS in FP16 and FP32. RTX A4500 achieves 19.2 TFLOPS in both precisions, making RTX 3080 55 percent faster theoretically.
How do cloud prices compare for RTX 3080 and RTX A4500?▾
RTX 3080 rents from $0.06/hr (average $0.13/hr) across 4 offers. RTX A4500 starts at $0.10/hr (average $0.19/hr) across 4 offers, favoring RTX 3080 on cost.
What are the TDPs of RTX 3080 and RTX A4500?▾
RTX 3080 requires 320W TDP, while RTX A4500 uses 140W. Lower TDP on A4500 supports efficient multi-GPU cloud configurations.
Do RTX 3080 and RTX A4500 share the same architecture?▾
Both employ Ampere architecture in PCIe form factors: RTX 3080 from 2020, A4500 from 2021. They offer comparable tensor core support for AI.
Which is better for high-bandwidth ML tasks?▾
RTX 3080 excels with 760 GB/s bandwidth versus A4500's 448 GB/s. This boosts batch processing in training and larger datasets.
Which is cheaper to rent, the RTX 3080 or the RTX A4000?▾
Cloud rental prices for both the RTX 3080 and RTX A4000 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 3080 have compared to the RTX A4000?▾
The RTX 3080 has 10 to 12 GB of GDDR6X memory. The RTX A4000 has 16 GB of GDDR6 memory.
Can I find RTX 3080 and RTX A4000 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 3080 and the RTX A4000?▾
The RTX 3080 uses the Ampere architecture (2020) while the RTX A4000 uses Ampere (2021). The RTX 3080 delivers 1.6x the FP16 throughput and 1.7x the memory bandwidth of the RTX A4000.