Specifications Compared
| Spec | A10 | RTX-3080 |
|---|---|---|
| TDP | 150W | 320W |
| VRAM | 24 GB | 10-12 GB |
| CUDA Cores | 9,216 | 8,704 |
| Memory Type | GDDR6 | GDDR6X |
| Architecture | Ampere | Ampere |
| Form Factors | PCIe | PCIe |
| Interconnect | ||
| Tensor Cores | 288 | 272 |
| FP16 Performance | 31.2 TFLOPS | 29.8 TFLOPS |
| FP32 Performance | 31.2 TFLOPS | 29.8 TFLOPS |
| INT8 Performance | 250 TOPS | |
| Memory Bandwidth | 600 GB/s | 760 GB/s |
Performance Analysis
The A10's 24 GB VRAM enables handling larger models or batch sizes in training and inference compared to the RTX 3080 Ti's 12 GB limit, reducing the need for model sharding in LLM fine-tuning. FP16 performance stands at 31.2 TFLOPS for the A10 and 29.8 TFLOPS for the RTX 3080 Ti, indicating similar tensor core throughput for half-precision deep learning tasks; the A10's matching 31.2 TFLOPS FP32 suits compute-bound scientific simulations better than the RTX 3080 Ti's 29.8 TFLOPS.
Higher memory bandwidth on the RTX 3080 Ti, at 760 GB/s versus 600 GB/s, accelerates data-heavy operations like image generation, allowing larger effective batch sizes in bandwidth-constrained scenarios. The A10's lower 150W TDP supports denser cloud deployments, while the RTX 3080 Ti's 320W demands more cooling and power infrastructure. These specs translate to the A10 favoring VRAM-bound workloads and the RTX 3080 Ti excelling in bandwidth-sensitive consumer AI.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
A10
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 LeaderGPU | 10×NVIDIA A10 24GB VRAM | 24GB | 64 vCPU 384GB RAM 2000GB Storage | Netherlands | $0.60/GPU/hr $6.00/hr total (10×) | Available | ||
 Vast.ai | 2×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 256 vCPU 126GB RAM 769GB Storage | Slovenia | $0.73/GPU/hr $1.47/hr total (2×) | Available | ||
Vast.ai | 2×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 256 vCPU 126GB RAM 5672GB Storage | Slovenia | $0.73/GPU/hr $1.47/hr total (2×) | Available | ||
LeaderGPU | 8×NVIDIA A100 PCIe 80GB 80GB VRAM | 80GB | 64 vCPU 384GB RAM 2000GB Storage | Netherlands | $0.90/GPU/hr $7.20/hr total (8×) | Available | ||
Vast.ai | 2×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 64 vCPU 126GB RAM 1114GB Storage | Czechia | $1.00/GPU/hr $2.00/hr total (2×) | Available |
When to Choose the A10
The A10 suits memory-constrained machine learning workflows: its 24 GB GDDR6 VRAM handles large LLMs during inference or fine-tuning without offloading, unlike the RTX 3080 Ti's 12 GB limit. Lower 150W TDP enables efficient multi-GPU clusters in datacenters, ideal for sustained professional training runs.
When to Choose the RTX 3080 Ti
The RTX 3080 Ti fits budget-driven projects: cloud pricing starts at $0.08/hr versus the A10's $0.60/hr, offering strong value for gaming-adjacent AI like Stable Diffusion. Its 760 GB/s bandwidth outperforms the A10's 600 GB/s in data-transfer intensive tasks, benefiting high-throughput inference on smaller models.
Use Cases
The A10's 24 GB VRAM supports larger batch sizes and models during training, exceeding the RTX 3080 Ti's 12 GB capacity. This reduces overhead from gradient checkpointing.
Smaller models fit both GPUs, but A10 handles up to 24 GB contexts while RTX 3080 Ti suffices for 12 GB with lower $0.08/hr costs. Choice depends on model size.
A10's 24 GB VRAM and 31.2 TFLOPS FP16/FP32 enable efficient fine-tuning of mid-sized LLMs without memory swaps. RTX 3080 Ti limits batches at 12 GB.
RTX 3080 Ti's 760 GB/s bandwidth accelerates image generation pipelines over A10's 600 GB/s. Consumer optimizations and $0.08/hr pricing enhance throughput.
A10's balanced 31.2 TFLOPS FP32 matches FP16 for simulations, paired with 24 GB VRAM for large datasets. Lower 150W TDP aids long runs.
Frequently Asked Questions
Which GPU has more VRAM: A10 or RTX 3080 Ti?▾
The A10 provides 24 GB GDDR6 VRAM, twice the RTX 3080 Ti's 12 GB GDDR6X. This makes the A10 better for large-model ML tasks. RTX 3080 Ti suffices for smaller workloads.
How do their memory bandwidths compare?▾
RTX 3080 Ti offers 760 GB/s, surpassing A10's 600 GB/s. Higher bandwidth benefits data-intensive inference. A10 compensates with more VRAM.
What are the FP16 performance differences?▾
A10 delivers 31.2 TFLOPS FP16, slightly above RTX 3080 Ti's 29.8 TFLOPS. Both excel in tensor operations for AI. Difference is under 5 percent.
Which is cheaper in the cloud?▾
RTX 3080 Ti starts at $0.08/hr (average $0.14/hr across 4 offers), far below A10's $0.60/hr (average $1.06/hr across 3 offers). Ti wins on cost.
Compare their power consumption.▾
A10 uses 150W TDP, half the RTX 3080 Ti's 320W. A10 supports denser deployments. RTX 3080 Ti requires more power infrastructure.
Are both suitable for PCIe cloud instances?▾
Yes, both use PCIe form factors. A10 targets datacenters, RTX 3080 Ti adapts from consumer setups. Compatibility is identical.
Which is cheaper to rent, the A10 or the RTX 3080?▾
Cloud rental prices for both the A10 and RTX 3080 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 A10 have compared to the RTX 3080?▾
The A10 has 24 GB of GDDR6 memory. The RTX 3080 has 10 to 12 GB of GDDR6X memory.
Can I find A10 and RTX 3080 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 A10 and the RTX 3080?▾
The A10 uses the Ampere architecture (2021) while the RTX 3080 uses Ampere (2020). The A10 delivers 1.0x the FP16 throughput and 1.3x the memory bandwidth of the RTX 3080.