Specifications Compared
| Spec | A10 | RTX-4070 |
|---|---|---|
| TDP | 150W | 200W |
| VRAM | 24 GB | 12 GB |
| CUDA Cores | 9,216 | 5,888 |
| Memory Type | GDDR6 | GDDR6X |
| Architecture | Ampere | Ada Lovelace |
| Form Factors | PCIe | PCIe |
| Interconnect | ||
| Tensor Cores | 288 | 184 |
| FP16 Performance | 31.2 TFLOPS | 29.1 TFLOPS |
| FP32 Performance | 31.2 TFLOPS | 29.1 TFLOPS |
| INT8 Performance | 250 TOPS | 466 TOPS |
| Memory Bandwidth | 600 GB/s | 504 GB/s |
Performance Analysis
Memory specifications define key advantages in practical applications. The A10's 24 GB VRAM doubles the RTX 4070 Ti's 12 GB, accommodating larger models or batch sizes up to 64 in LLM training without out-of-memory errors. Higher 600 GB/s bandwidth versus 504 GB/s minimizes latency in data transfers, enhancing throughput for memory-bound tasks like fine-tuning.
Compute parity appears close, as A10 delivers 31.2 TFLOPS FP16 and FP32 against RTX 4070 Ti's 29.1 TFLOPS each, supporting efficient mixed-precision operations in both training and inference. For training, A10's capacity enables bigger batches reducing wall-clock time; inference benefits from Ada Lovelace efficiencies despite specs showing marginal TFLOPS gap. Lower 150 W TDP on A10 aids dense server cooling compared to 200 W.
Overall, A10 suits high-memory demands, while RTX 4070 Ti leverages newer architecture for cost-effective general compute.
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 5672GB 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 769GB 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 |
RTX 4070 Ti
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA GeForce RTX 4070 Ti 12GB VRAM | 12GB | 6 vCPU 30GB RAM | 🌍global | $0.50/GPU/hr |
When to Choose the A10
Opt for the NVIDIA A10 when memory constraints dominate workloads. Its 24 GB GDDR6 VRAM handles large LLMs or scientific simulations exceeding 12 GB, with 600 GB/s bandwidth sustaining high batch sizes. The 31.2 TFLOPS FP16/FP32 performance and 150 W TDP make it reliable for sustained datacenter training at $0.60 to $1.06 per hour.
When to Choose the RTX 4070 Ti
Select the NVIDIA GeForce RTX 4070 Ti for budget-driven projects. Priced from $0.08 per hour averaging $0.22 per hour, it offers 29.1 TFLOPS FP16/FP32 on Ada Lovelace, ideal for inference or Stable Diffusion within 12 GB VRAM limits. Newer architecture provides efficiency gains despite 200 W TDP and 504 GB/s bandwidth.
Use Cases
A10's 24 GB VRAM supports larger models and batch sizes exceeding RTX 4070 Ti's 12 GB capacity. Higher 600 GB/s bandwidth reduces training bottlenecks.
RTX 4070 Ti's lower $0.08 per hour pricing scales inference deployments efficiently. 12 GB VRAM and 29.1 TFLOPS suffice for typical serving loads.
A10 handles fine-tuning of memory-intensive models with 24 GB VRAM versus 12 GB. 31.2 TFLOPS FP16 aids faster iterations.
RTX 4070 Ti excels in generative tasks via Ada Lovelace optimizations at $0.22 per hour average. 504 GB/s bandwidth supports image generation pipelines.
A10's 600 GB/s bandwidth and 24 GB VRAM accelerate simulations with large datasets. Lower 150 W TDP fits prolonged compute runs.
Frequently Asked Questions
Which has more VRAM: A10 or RTX 4070 Ti?▾
The NVIDIA A10 provides 24 GB GDDR6 VRAM, double the NVIDIA GeForce RTX 4070 Ti's 12 GB GDDR6X. This makes A10 better for memory-heavy tasks. RTX 4070 Ti suits lighter workloads.
How do TFLOPS compare between A10 and RTX 4070 Ti?▾
A10 achieves 31.2 TFLOPS in both FP16 and FP32, slightly above RTX 4070 Ti's 29.1 TFLOPS per metric. Differences impact high-precision compute marginally. Both support tensor operations effectively.
What are the cloud prices for A10 vs RTX 4070 Ti?▾
A10 rents from $0.60 per hour, averaging $1.06 per hour across three offers. RTX 4070 Ti starts at $0.08 per hour, averaging $0.22 per hour across five offers. RTX 4070 Ti offers better value per hour.
Which GPU has higher memory bandwidth?▾
NVIDIA A10 delivers 600 GB/s bandwidth with GDDR6, exceeding RTX 4070 Ti's 504 GB/s on GDDR6X. A10 reduces data transfer delays in training. RTX 4070 Ti remains competitive for inference.
Compare TDP of A10 and RTX 4070 Ti?▾
A10 consumes 150 W TDP, lower than RTX 4070 Ti's 200 W. This favors A10 in power-constrained clouds. Efficiency per watt varies by architecture.
A10 vs RTX 4070 Ti architecture?▾
A10 uses Ampere from 2021, RTX 4070 Ti employs Ada Lovelace from 2023. Ada provides newer features like improved RT cores. Compute specs show A10 slightly ahead at 31.2 TFLOPS.
Which is cheaper to rent, the A10 or the RTX 4070?▾
Cloud rental prices for both the A10 and RTX 4070 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 4070?▾
The A10 has 24 GB of GDDR6 memory. The RTX 4070 has 12 GB of GDDR6X memory.
Can I find A10 and RTX 4070 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 4070?▾
The A10 uses the Ampere architecture (2021) while the RTX 4070 uses Ada Lovelace (2023). The A10 delivers 1.1x the FP16 throughput and 1.2x the memory bandwidth of the RTX 4070.