Specifications Compared
| Spec | A100 | RTX-4060 |
|---|---|---|
| TDP | 400W | 115W |
| VRAM | 40-80 GB | 8 GB |
| CUDA Cores | 6,912 | 3,072 |
| Memory Type | HBM2e | GDDR6 |
| Architecture | Ampere | Ada Lovelace |
| Form Factors | SXM4, PCIe | PCIe |
| Interconnect | NVLink, PCIe 4.0, InfiniBand | |
| Tensor Cores | 432 | 96 |
| FP16 Performance | 312 TFLOPS | 15.1 TFLOPS |
| FP32 Performance | 19.5 TFLOPS | 15.1 TFLOPS |
| FP64 Performance | 9.7 TFLOPS | |
| INT8 Performance | 624 TOPS | 242 TOPS |
| Memory Bandwidth | 2,039 GB/s | 272 GB/s |
Performance Analysis
The A100's FP16 performance reaches 312 TFLOPS, dwarfing the RTX 4060's 15.1 TFLOPS: this enables the A100 to accelerate deep learning training with mixed-precision formats far more effectively. For inference, the high FP16 rate supports larger batch sizes without precision loss. The A100's FP32 of 19.5 TFLOPS edges out the RTX 4060's equal 15.1 TFLOPS in FP16/FP32, but the consumer card's balanced ratios suit graphics over tensor-heavy tasks.
Memory bandwidth defines real-world limits: the A100's 2039 GB/s sustains massive models and datasets, allowing batch sizes up to 40 GB VRAM capacity, ideal for LLM training. The RTX 4060's 272 GB/s restricts it to smaller batches, risking out-of-memory errors beyond 8 GB. TDP differences, 400W versus 115W, reflect datacenter scaling potential against desktop constraints, impacting multi-GPU clusters via NVLink on the A100.
These specs translate to the A100 dominating HPC while the RTX 4060 handles lightweight AI efficiently.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
A100 SXM4 40GB
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 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 557GB Storage | Czechia | $1.00/GPU/hr | Available | ||
 Denvr | 4×NVIDIA A100 PCIe 80GB 80GB VRAM | 80GB | 64 vCPU 512GB RAM 7600GB Storage | Virginia | $1.15/GPU/hr $4.60/hr total (4×) |
When to Choose the A100 SXM4 40GB
Select the A100 SXM4 40GB for large-scale AI training or scientific simulations demanding over 8 GB VRAM. Its 312 TFLOPS FP16 and 2039 GB/s bandwidth enable handling of models like 70B-parameter LLMs with large batches. NVLink and InfiniBand interconnects make it superior for multi-GPU clusters in cloud environments starting at $1.00 per hour.
When to Choose the RTX 4060
Choose the RTX 4060 for consumer desktops running Stable Diffusion or small-model inference where 8 GB GDDR6 and 15.1 TFLOPS FP16 suffice. Its 115W TDP ensures low power use without datacenter overhead, and Ada Lovelace efficiency boosts gaming alongside light AI. Absence of cloud pricing favors local setups.
Use Cases
The A100's 40 GB VRAM and 312 TFLOPS FP16 handle massive datasets and models exceeding 8 GB limits. RTX 4060 cannot support large batch sizes due to 272 GB/s bandwidth.
High 2039 GB/s bandwidth on A100 enables efficient large-batch serving. RTX 4060's 8 GB VRAM restricts model sizes.
A100's superior FP16 performance and memory capacity accelerate parameter-efficient fine-tuning on big models. RTX 4060 lacks VRAM for complex adapters.
RTX 4060's Ada architecture and 15.1 TFLOPS FP16 optimize image generation at 8 GB scale. Lower 115W TDP suits desktop use over A100's 400W.
A100's 19.5 TFLOPS FP32 and NVLink excel in simulations needing high precision and multi-GPU scaling. RTX 4060's specs limit HPC workloads.
Frequently Asked Questions
What is the VRAM difference between A100 SXM4 40GB and RTX 4060?▾
The A100 provides 40 GB HBM2e VRAM, far exceeding the RTX 4060's 8 GB GDDR6. This allows the A100 to load larger models without swapping. Bandwidth follows suit at 2039 GB/s versus 272 GB/s.
How do FP16 performances compare?▾
A100 delivers 312 TFLOPS FP16, over 20 times the RTX 4060's 15.1 TFLOPS. This gap accelerates ML training on A100. FP32 is closer at 19.5 TFLOPS versus 15.1 TFLOPS.
What are the power requirements?▾
The A100 SXM4 draws 400W TDP for datacenter use, while RTX 4060 uses 115W for desktops. A100 suits clusters; RTX 4060 fits low-power setups. No cloud pricing for RTX 4060 currently.
Is A100 available on cloud platforms?▾
A100 SXM4 40GB starts at $1.00 per hour, averaging $2.53 across six providers. RTX 4060 has no live cloud offers. Check gpuperhour.com for updates.
Which has better memory bandwidth?▾
A100's 2039 GB/s vastly outpaces RTX 4060's 272 GB/s. This supports bigger batches on A100 for training. RTX 4060 handles smaller workloads adequately.
What architectures do they use?▾
A100 employs Ampere from 2020; RTX 4060 uses Ada Lovelace from 2023. A100 prioritizes tensor cores; RTX 4060 balances gaming and AI. Form factors differ: SXM4/PCIe versus PCIe.
Which is cheaper to rent, the A100 or the RTX 4060?▾
Cloud rental prices for both the A100 and RTX 4060 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 A100 have compared to the RTX 4060?▾
The A100 has 40 to 80 GB of HBM2e memory. The RTX 4060 has 8 GB of GDDR6 memory.
Can I find A100 and RTX 4060 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 A100 and the RTX 4060?▾
The A100 uses the Ampere architecture (2020) while the RTX 4060 uses Ada Lovelace (2023). The A100 delivers 20.7x the FP16 throughput and 7.5x the memory bandwidth of the RTX 4060.