Specifications Compared
| Spec | A10 | QUADRO-RTX-5000 |
|---|---|---|
| TDP | 150W | 230W |
| VRAM | 24 GB | 16 GB |
| CUDA Cores | 9,216 | 3,072 |
| Memory Type | GDDR6 | GDDR6 |
| Architecture | Ampere | Turing |
| Form Factors | PCIe | PCIe |
| Interconnect | NVLink | |
| Tensor Cores | 288 | 384 |
| FP16 Performance | 31.2 TFLOPS | 11.2 TFLOPS |
| FP32 Performance | 31.2 TFLOPS | 11.2 TFLOPS |
| INT8 Performance | 250 TOPS | |
| Memory Bandwidth | 600 GB/s | 448 GB/s |
Performance Analysis
The A10 delivers 31.2 TFLOPS in FP16 and FP32 performance, nearly three times the Quadro RTX 5000's 11.2 TFLOPS: this gap translates to faster neural network training, where FP16 accelerates matrix multiplications, and inference, benefiting from higher tensor core throughput. Real-world training times reduce significantly on the A10 for models like transformers.
VRAM capacity of 24 GB on the A10 versus 16 GB on the Quadro allows larger batch sizes in deep learning: bigger batches improve GPU utilization and speed up iterations without out-of-memory errors. Memory bandwidth reaches 600 GB/s on the A10 compared to 448 GB/s, minimizing data transfer delays in bandwidth-intensive operations such as image processing or simulations.
Power efficiency favors the A10 at 150W TDP over the Quadro's 230W: lower consumption suits dense cloud deployments while delivering superior compute density.
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 |
Quadro RTX 5000
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Paperspace | NVIDIA Quadro RTX 5000 16GB VRAM | 16GB | 8 vCPU 30GB RAM 50GB Storage | New York | $0.82/GPU/hr | Available | ||
Paperspace | 2×NVIDIA Quadro RTX 5000 16GB VRAM | 16GB | 16 vCPU 60GB RAM 50GB Storage | New York | $0.82/GPU/hr $1.64/hr total (2×) | Available |
When to Choose the A10
Select the A10 for AI training, inference, and generative tasks demanding high memory and compute. Its 24 GB VRAM and 31.2 TFLOPS FP32 handle large models and batches effectively, with 600 GB/s bandwidth ensuring smooth data flow. Starting at $0.60 per hour, it provides strong value for modern workloads.
The A10's Ampere architecture outperforms Turing-based alternatives in tensor operations, making it ideal for cloud-scale ML deployments.
When to Choose the Quadro RTX 5000
Choose the Quadro RTX 5000 for professional CAD, rendering, or visualization where NVLink enables multi-GPU connectivity. Its 16 GB VRAM suffices for complex 3D scenes, and PCIe compatibility fits workstation emulation in cloud setups at a flat $0.82 per hour average.
Legacy software optimized for Turing excels on the Quadro, avoiding recompilation needs for Quadro-specific features.
Use Cases
The A10's 31.2 TFLOPS FP16 and 24 GB VRAM support larger models and batches than the Quadro RTX 5000's 11.2 TFLOPS and 16 GB. Higher bandwidth of 600 GB/s accelerates data loading for extended training runs.
A10 achieves 31.2 TFLOPS FP32 for faster token generation on large language models versus Quadro's 11.2 TFLOPS. 24 GB VRAM handles bigger contexts without quantization.
A10's superior 31.2 TFLOPS and 24 GB VRAM enable efficient fine-tuning of models over 16 GB limits on Quadro RTX 5000. Lower 150W TDP aids prolonged sessions.
24 GB VRAM on A10 supports high-resolution image generation at 31.2 TFLOPS, outperforming Quadro's 16 GB and 11.2 TFLOPS for diffusion models.
A10's 600 GB/s bandwidth and 31.2 TFLOPS FP32 excel in simulations over Quadro's 448 GB/s and 11.2 TFLOPS. NVLink on Quadro may suit rare multi-GPU sims, but A10 wins broadly.
Frequently Asked Questions
Which GPU has more VRAM, A10 or Quadro RTX 5000?▾
The A10 provides 24 GB GDDR6 VRAM, exceeding the Quadro RTX 5000's 16 GB. This difference allows the A10 to manage larger datasets or models. Batch sizes increase accordingly in memory-bound tasks.
How do FP32 performance levels compare between A10 and Quadro RTX 5000?▾
A10 reaches 31.2 TFLOPS FP32, nearly three times the Quadro RTX 5000's 11.2 TFLOPS. Training and simulations run faster on A10. Inference latency drops with higher throughput.
What are the current cloud rental prices for these GPUs?▾
A10 starts from $0.60 per hour, averaging $1.06 across three offers. Quadro RTX 5000 averages $0.82 per hour across two offers. Prices fluctuate based on providers.
Does the Quadro RTX 5000 support NVLink?▾
Yes, the Quadro RTX 5000 includes NVLink interconnect for multi-GPU scaling. A10 lacks this feature. NVLink benefits parallel rendering tasks.
Which GPU is more power efficient?▾
A10 consumes 150W TDP, lower than Quadro RTX 5000's 230W. A10 delivers higher 31.2 TFLOPS at reduced power. This suits dense cloud instances.
What architectures power these GPUs?▾
A10 uses Ampere from 2021 with tensor cores optimized for AI. Quadro RTX 5000 employs Turing from 2018. Ampere provides generational compute uplift.
Which is cheaper to rent, the A10 or the Quadro RTX 5000?▾
Cloud rental prices for both the A10 and Quadro RTX 5000 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 Quadro RTX 5000?▾
The A10 has 24 GB of GDDR6 memory. The Quadro RTX 5000 has 16 GB of GDDR6 memory.
Can I find A10 and Quadro RTX 5000 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 Quadro RTX 5000?▾
The A10 uses the Ampere architecture (2021) while the Quadro RTX 5000 uses Turing (2018). The A10 delivers 2.8x the FP16 throughput and 1.3x the memory bandwidth of the Quadro RTX 5000.