Specifications Compared
| Spec | A100 | RTX-4080 |
|---|---|---|
| TDP | 400W | 320W |
| VRAM | 40-80 GB | 16 GB |
| CUDA Cores | 6,912 | 9,728 |
| Memory Type | HBM2e | GDDR6X |
| Architecture | Ampere | Ada Lovelace |
| Form Factors | SXM4, PCIe | PCIe |
| Interconnect | NVLink, PCIe 4.0, InfiniBand | |
| Tensor Cores | 432 | 304 |
| FP16 Performance | 312 TFLOPS | 48.7 TFLOPS |
| FP32 Performance | 19.5 TFLOPS | 48.7 TFLOPS |
| FP64 Performance | 9.7 TFLOPS | |
| INT8 Performance | 624 TOPS | 780 TOPS |
| Memory Bandwidth | 2,039 GB/s | 717 GB/s |
Performance Analysis
The A100 SXM4 40GB excels in FP16 workloads at 312 TFLOPS: this delivers up to 6.4 times the half-precision throughput of the RTX 4080 SUPER's 48.7 TFLOPS, accelerating mixed-precision training for large neural networks. The RTX 4080 SUPER leads in FP32 at 48.7 TFLOPS versus the A100's 19.5 TFLOPS: this benefits single-precision tasks like graphics rendering or certain simulations.
Memory bandwidth defines batch size capabilities: the A100's 2039 GB/s supports larger datasets and models without out-of-memory errors, enabling efficient training of LLMs exceeding 16 GB VRAM limits on the RTX 4080 SUPER. The RTX 4080 SUPER's 717 GB/s suffices for smaller inference runs but bottlenecks high-throughput scenarios.
Power draw reflects workload intensity: the A100 consumes 400W TDP for sustained datacenter performance, while the 320W RTX 4080 SUPER suits cost-sensitive, intermittent use.
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 646GB Storage | Czechia | $1.07/GPU/hr | Available | ||
 Denvr | 8×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 128 vCPU 1024GB RAM 15200GB Storage | Virginia | $1.15/GPU/hr $9.20/hr total (8×) |
RTX 4080 SUPER
| 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 A100 SXM4 40GB
The A100 SXM4 40GB suits large-scale machine learning training: its 40 GB HBM2e VRAM handles models that exceed the RTX 4080 SUPER's 16 GB capacity. High memory bandwidth of 2039 GB/s supports massive batch sizes in distributed setups via NVLink and InfiniBand interconnects.
Enterprise environments favor the A100 for FP16-dominant tasks: 312 TFLOPS performance speeds LLM fine-tuning and scientific simulations where precision and scale matter most.
When to Choose the RTX 4080 SUPER
The RTX 4080 SUPER fits budget-conscious inference and creative workloads: its average cloud price of $0.32 per hour undercuts the A100's $1.78 per hour. Balanced 48.7 TFLOPS FP16 and FP32 performance handles Stable Diffusion or gaming-related compute efficiently.
Prosumer users select the RTX 4080 SUPER for 16 GB VRAM tasks: 717 GB/s bandwidth and 320W TDP enable rapid prototyping without datacenter overhead.
Use Cases
The A100's 40 GB VRAM and 312 TFLOPS FP16 support large models and fast mixed-precision training. The RTX 4080 SUPER's 16 GB limits scale.
2039 GB/s bandwidth on the A100 enables high batch sizes for production inference. RTX 4080 SUPER suits small models only.
40 GB HBM2e VRAM accommodates full model loading during fine-tuning. 312 TFLOPS FP16 accelerates iterations.
RTX 4080 SUPER's Ada architecture and 48.7 TFLOPS FP32 optimize image generation. Lower $0.32 per hour average cost fits iterative use.
A100's high FP16 at 312 TFLOPS and NVLink interconnect speed HPC simulations. Bandwidth of 2039 GB/s handles large datasets.
Frequently Asked Questions
Which GPU has more VRAM?▾
The A100 SXM4 40GB provides 40 GB HBM2e VRAM. The RTX 4080 SUPER offers 16 GB GDDR6X. This difference impacts large model handling.
What are the cloud pricing differences?▾
A100 SXM4 40GB starts at $0.13 per hour, averaging $1.78 per hour across 10 offers. RTX 4080 SUPER begins at $0.17 per hour, averaging $0.32 per hour over 3 offers.
Which is better for LLM training?▾
The A100 excels with 312 TFLOPS FP16 and 40 GB VRAM for large-scale training. RTX 4080 SUPER's 48.7 TFLOPS and 16 GB limit it to smaller models.
How do memory bandwidths compare?▾
A100 SXM4 40GB delivers 2039 GB/s for high-throughput tasks. RTX 4080 SUPER provides 717 GB/s, suitable for moderate workloads.
What are the TDP ratings?▾
The A100 consumes 400W TDP for datacenter performance. RTX 4080 SUPER uses 320W, aiding efficiency in prosumer setups.
Which architecture is newer?▾
RTX 4080 SUPER uses Ada Lovelace from 2022. A100 employs Ampere from 2020, optimized for enterprise compute.
Which is cheaper to rent, the A100 or the RTX 4080?▾
Cloud rental prices for both the A100 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 A100 have compared to the RTX 4080?▾
The A100 has 40 to 80 GB of HBM2e memory. The RTX 4080 has 16 GB of GDDR6X memory.
Can I find A100 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 A100 and the RTX 4080?▾
The A100 uses the Ampere architecture (2020) while the RTX 4080 uses Ada Lovelace (2022). The A100 delivers 6.4x the FP16 throughput and 2.8x the memory bandwidth of the RTX 4080.