Specifications Compared
| Spec | A10 | RTX-4080 |
|---|---|---|
| TDP | 150W | 320W |
| VRAM | 24 GB | 16 GB |
| CUDA Cores | 9,216 | 9,728 |
| Memory Type | GDDR6 | GDDR6X |
| Architecture | Ampere | Ada Lovelace |
| Form Factors | PCIe | PCIe |
| Interconnect | ||
| Tensor Cores | 288 | 304 |
| FP16 Performance | 31.2 TFLOPS | 48.7 TFLOPS |
| FP32 Performance | 31.2 TFLOPS | 48.7 TFLOPS |
| INT8 Performance | 250 TOPS | 780 TOPS |
| Memory Bandwidth | 600 GB/s | 717 GB/s |
Performance Analysis
The RTX 4080 demonstrates superior raw compute with 48.7 TFLOPS in FP16 and FP32, compared to the A10's 31.2 TFLOPS: this translates to approximately 56 percent faster performance in training and inference for deep learning models reliant on half-precision or single-precision arithmetic. Higher FP16 throughput on the RTX 4080 accelerates matrix multiplications common in transformer-based models, reducing epoch times in training scenarios.
Memory bandwidth plays a critical role in handling large batch sizes: the RTX 4080's 717 GB/s exceeds the A10's 600 GB/s by 19.5 percent, enabling smoother data flow for inference at scale and minimizing bottlenecks in memory-bound operations. However, the A10's 24 GB VRAM capacity supports larger models or bigger batches without swapping, unlike the RTX 4080's 16 GB limit. The RTX 4080's 320W TDP demands more power than the A10's 150W, potentially increasing operational costs in dense cloud setups.
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 |
RTX 4080
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA GeForce RTX 4080 SUPER 16GB VRAM | 16GB | 6 vCPU 35GB RAM | 🌍global | $0.50/GPU/hr | |||
RunPod | NVIDIA GeForce RTX 4080 16GB VRAM | 16GB | 6 vCPU 35GB RAM | 🌍global | $0.50/GPU/hr |
When to Choose the A10
The A10 excels in scenarios requiring substantial VRAM, such as loading large language models exceeding 16 GB: its 24 GB GDDR6 capacity prevents out-of-memory errors during fine-tuning or inference on models like Llama 70B. Lower TDP at 150W suits power-constrained environments or multi-GPU nodes where thermal limits matter. At an average of $1.06 per hour, it provides reliability for enterprise workloads prioritizing memory over peak speed.
When to Choose the RTX 4080
The RTX 4080 stands out for compute-intensive tasks due to its 48.7 TFLOPS FP16 and FP32 rates, delivering 56 percent more throughput than the A10's 31.2 TFLOPS for faster training iterations. Superior 717 GB/s bandwidth supports high-batch inference efficiently. With pricing from $0.11 per hour and an average of $0.28, it offers unmatched value for budget-sensitive users on modern Ada architecture.
Use Cases
The RTX 4080's 48.7 TFLOPS FP16 outperforms the A10's 31.2 TFLOPS by 56 percent, accelerating gradient computations. Its lower $0.28 average hourly rate enhances affordability for extended training runs.
A10's 24 GB VRAM handles larger models without quantization issues, unlike RTX 4080's 16 GB limit. Bandwidth at 600 GB/s suffices for batch inference where memory capacity dominates.
RTX 4080 offers speed via 48.7 TFLOPS for quick iterations, while A10's 24 GB VRAM supports bigger datasets. Choice depends on model size versus budget at $0.28 versus $1.06 per hour.
RTX 4080's Ada architecture and 717 GB/s bandwidth generate images faster than A10's Ampere setup. Pricing from $0.11 per hour makes it economical for high-volume creative workloads.
A10's 24 GB VRAM accommodates large simulation datasets, with 150W TDP fitting multi-node clusters. Stable 31.2 TFLOPS FP32 performance suits precision numerical tasks.
Frequently Asked Questions
Which has more VRAM, A10 or RTX 4080?▾
The A10 provides 24 GB GDDR6 VRAM, exceeding the RTX 4080's 16 GB GDDR6X. This advantage aids memory-heavy tasks like large model inference. Bandwidth differs at 600 GB/s for A10 versus 717 GB/s for RTX 4080.
What is the performance difference in TFLOPS?▾
RTX 4080 delivers 48.7 TFLOPS in FP16 and FP32, while A10 offers 31.2 TFLOPS in each: a 56 percent lead for RTX 4080. This impacts training speed significantly. Architectures are Ampere for A10 and Ada Lovelace for RTX 4080.
How do cloud prices compare for A10 vs RTX 4080?▾
RTX 4080 starts at $0.11 per hour with $0.28 average across eight offers; A10 begins at $0.60 with $1.06 average across three. RTX 4080 provides better value. Prices reflect live gpuperhour.com data.
Which GPU has higher TDP?▾
RTX 4080 consumes 320W TDP, double the A10's 150W. Higher TDP correlates with RTX 4080's 48.7 TFLOPS performance. Both use PCIe form factors.
Is RTX 4080 faster for AI inference?▾
Yes, RTX 4080's 717 GB/s bandwidth and 48.7 TFLOPS enable larger batches and quicker responses than A10's 600 GB/s and 31.2 TFLOPS. VRAM limits RTX 4080 to 16 GB models. Newer Ada architecture contributes to efficiency.
Can A10 handle bigger models than RTX 4080?▾
A10's 24 GB VRAM supports models up to that size without issues, surpassing RTX 4080's 16 GB. This suits unquantized LLMs. Performance trades off at 31.2 TFLOPS versus 48.7.
Which is cheaper to rent, the A10 or the RTX 4080?▾
Cloud rental prices for both the A10 and RTX 4080 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 4080?▾
The A10 has 24 GB of GDDR6 memory. The RTX 4080 has 16 GB of GDDR6X memory.
Can I find A10 and RTX 4080 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 4080?▾
The A10 uses the Ampere architecture (2021) while the RTX 4080 uses Ada Lovelace (2022). The RTX 4080 delivers 1.6x the FP16 throughput and 1.2x the memory bandwidth of the A10.