Specifications Compared
| Spec | A10 | RTX-5070 |
|---|---|---|
| TDP | 150W | 250W |
| VRAM | 24 GB | 12 GB |
| CUDA Cores | 9,216 | 6,144 |
| Memory Type | GDDR6 | GDDR7 |
| Architecture | Ampere | Blackwell |
| Form Factors | PCIe | PCIe |
| Interconnect | ||
| Tensor Cores | 288 | 192 |
| FP16 Performance | 31.2 TFLOPS | 40.6 TFLOPS |
| FP32 Performance | 31.2 TFLOPS | 40.6 TFLOPS |
| INT8 Performance | 250 TOPS | 650 TOPS |
| Memory Bandwidth | 600 GB/s | 448 GB/s |
Performance Analysis
Compute performance shows the RTX 5070 ahead: its 40.6 TFLOPS in FP16 and FP32 surpasses the A10's 31.2 TFLOPS by 30 percent, benefiting training and inference in compute-bound workloads. This delta means faster iterations for models like transformers where half-precision FP16 accelerates matrix operations without accuracy loss.
Memory specs favor the A10 for memory-intensive tasks: 24 GB VRAM supports larger models or batch sizes than the RTX 5070's 12 GB, while 600 GB/s bandwidth versus 448 GB/s enables higher throughput for data-heavy operations. Lower bandwidth on the RTX 5070 may limit batch sizes in training, causing out-of-memory errors sooner.
Power efficiency tilts toward the A10 with 150W TDP against 250W, reducing operational costs in dense cloud deployments. Newer Blackwell architecture in the RTX 5070 likely offers ancillary improvements in tensor cores, though specs emphasize raw TFLOPS gains.
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 | NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 256 vCPU 63GB RAM 2826GB Storage | Slovenia | $0.73/GPU/hr | Available | ||
Vast.ai | 2×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 256 vCPU 126GB RAM 794GB 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 | NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 64 vCPU 63GB RAM 646GB Storage | Czechia | $1.07/GPU/hr | Available |
When to Choose the A10
Choose the A10 for workloads demanding high VRAM capacity, such as training large language models exceeding 12 GB. Its 24 GB GDDR6 handles bigger batch sizes without splitting across GPUs, and 600 GB/s bandwidth sustains data flow effectively.
The A10 suits power-constrained environments: 150W TDP fits efficiently in multi-GPU servers, despite higher pricing from $0.60 per hour.
When to Choose the RTX 5070
Select the RTX 5070 for compute-heavy tasks like inference on smaller models, where 40.6 TFLOPS outperforms the A10's 31.2 TFLOPS. Lower pricing from $0.08 per hour makes it ideal for high-volume, cost-sensitive deployments.
Blackwell architecture benefits modern AI pipelines: GDDR7 memory and higher TFLOPS accelerate fine-tuning or diffusion models efficiently.
Use Cases
The A10's 24 GB VRAM supports larger models and batch sizes critical for LLM training, outperforming the RTX 5070's 12 GB limit. Higher 600 GB/s bandwidth prevents bottlenecks in data loading.
RTX 5070's 40.6 TFLOPS FP16 performance accelerates inference queries faster than the A10's 31.2 TFLOPS. Low $0.08 per hour pricing suits high-throughput serving.
Higher 40.6 TFLOPS on RTX 5070 speeds parameter updates over A10's 31.2 TFLOPS. Cost efficiency at average $0.21 per hour favors extended fine-tuning sessions.
Blackwell architecture and 40.6 TFLOPS enhance image generation speed beyond A10's capabilities. Affordable pricing from $0.08 per hour supports creative workflows.
A10's 24 GB VRAM aids large simulations, while RTX 5070's 40.6 TFLOPS FP32 boosts compute-intensive calculations. Choice depends on memory versus speed needs.
Frequently Asked Questions
Which GPU has more VRAM, A10 or RTX 5070?▾
The A10 offers 24 GB GDDR6 VRAM, doubling the RTX 5070's 12 GB GDDR7. This makes the A10 better for memory-bound tasks like large model training.
How do the TFLOPS compare between A10 and RTX 5070?▾
RTX 5070 delivers 40.6 TFLOPS in FP16 and FP32, exceeding A10's 31.2 TFLOPS by 30 percent. This advantage shines in compute-heavy inference.
What is the price difference for these GPUs in the cloud?▾
A10 pricing starts at $0.60 per hour averaging $1.06 across three offers, while RTX 5070 starts at $0.08 per hour averaging $0.21 across six offers. RTX 5070 provides far better cost efficiency.
Which has higher memory bandwidth?▾
A10 achieves 600 GB/s bandwidth, surpassing RTX 5070's 448 GB/s. Higher bandwidth on A10 supports larger batch sizes in training.
What are the TDP ratings?▾
A10 uses 150W TDP, lower than RTX 5070's 250W. A10 enables more efficient power usage in cloud servers.
Are both GPUs suitable for PCIe cloud instances?▾
Yes, both A10 and RTX 5070 use PCIe form factors. They integrate seamlessly into standard cloud GPU offerings.
Which is cheaper to rent, the A10 or the RTX 5070?▾
Cloud rental prices for both the A10 and RTX 5070 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 5070?▾
The A10 has 24 GB of GDDR6 memory. The RTX 5070 has 12 GB of GDDR7 memory.
Can I find A10 and RTX 5070 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 5070?▾
The A10 uses the Ampere architecture (2021) while the RTX 5070 uses Blackwell (2025). The RTX 5070 delivers 1.3x the FP16 throughput and 1.3x the memory bandwidth of the A10.