Specifications Compared
| Spec | A100 | RTX-A4000 |
|---|---|---|
| TDP | 400W | 140W |
| VRAM | 40-80 GB | 16 GB |
| CUDA Cores | 6,912 | 6,144 |
| Memory Type | HBM2e | GDDR6 |
| Architecture | Ampere | Ampere |
| Form Factors | SXM4, PCIe | PCIe |
| Interconnect | NVLink, PCIe 4.0, InfiniBand | |
| Tensor Cores | 432 | 192 |
| FP16 Performance | 312 TFLOPS | 19.2 TFLOPS |
| FP32 Performance | 19.5 TFLOPS | 19.2 TFLOPS |
| FP64 Performance | 9.7 TFLOPS | |
| INT8 Performance | 624 TOPS | |
| Memory Bandwidth | 2,039 GB/s | 448 GB/s |
Performance Analysis
A100 SXM4 80GB's 312 TFLOPS FP16 performance vastly outpaces RTX A4000's 19.2 TFLOPS, accelerating deep learning training where half-precision computations dominate: models train up to 16 times faster on A100 for FP16-heavy workloads like transformers. FP32 parity at 19.5 TFLOPS for A100 and 19.2 TFLOPS for A4000 means similar speeds for inference or simulations not leveraging tensor cores.
Memory specs dictate real-world viability: A100's 80 GB HBM2e and 2039 GB/s bandwidth enable enormous batch sizes in LLM training, loading models over 70 GB without offloading, while A4000's 16 GB GDDR6 and 448 GB/s cap batches at smaller scales, risking out-of-memory errors on complex datasets. Bandwidth superiority on A100 minimizes stalls in memory-intensive inference.
Power draw reveals trade-offs: A100's 400W TDP suits cooled datacenters, but A4000's 140W fits edge or multi-GPU workstations without excessive cooling demands.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
A100 SXM4 80GB
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vast.ai | NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 256 vCPU 63GB RAM 397GB Storage | Slovenia | $0.73/GPU/hr | 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 | ||
 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×) | |||
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 A4000
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 TensorDock | NVIDIA RTX A4000 16GB VRAM | 16GB | 0 vCPU 0GB RAM | Tallinn, Harjumaa | $0.08/GPU/hr | Available | ||
Vast.ai | 8×NVIDIA RTX A4000 16GB VRAM | 16GB | 80 vCPU 201GB RAM 1698GB Storage | United Kingdom | $0.15/GPU/hr $1.17/hr total (8×) | Available | ||
 Hyperstack | 4×NVIDIA RTX A4000 16GB VRAM | 16GB | 16 vCPU 86GB RAM 500GB Storage | Norway | $0.15/GPU/hr $0.60/hr total (4×) | Available | ||
Hyperstack | 2×NVIDIA RTX A4000 16GB VRAM | 16GB | 8 vCPU 43GB RAM 200GB Storage | Norway | $0.15/GPU/hr $0.30/hr total (2×) | Available | ||
Hyperstack | NVIDIA RTX A4000 16GB VRAM | 16GB | 4 vCPU 21GB RAM 100GB Storage | Norway | $0.15/GPU/hr | Available |
When to Choose the A100 SXM4 80GB
NVIDIA A100 SXM4 80GB excels in large-scale AI training and inference for models exceeding 16 GB VRAM. Its 312 TFLOPS FP16 and 2039 GB/s bandwidth support massive batches in LLM development, enabling full model fits and rapid iterations across distributed setups via NVLink. Datacenter users prioritize this for high-throughput production workloads.
When to Choose the RTX A4000
NVIDIA RTX A4000 fits budget-conscious inference, fine-tuning of small-to-medium models, and professional visualization. With 19.2 TFLOPS FP32/FP16 and 16 GB VRAM at $0.08 per hour starting price, it handles tasks like Stable Diffusion or batch inference efficiently. Lower 140W TDP aids dense cloud or workstation deployments without high power costs.
Use Cases
A100's 80 GB HBM2e VRAM and 312 TFLOPS FP16 support training massive LLMs with large batches, avoiding the 16 GB limit of A4000 that requires model sharding.
80 GB VRAM on A100 loads full large LLMs for low-latency serving, while A4000's 16 GB suits only quantized smaller variants.
High 2039 GB/s bandwidth and FP16 performance enable efficient fine-tuning on datasets needing substantial memory, outperforming A4000's 448 GB/s.
A4000's 16 GB GDDR6 suffices for image generation pipelines at 19.2 TFLOPS, with lower $0.08 per hour pricing ideal for creative workflows.
FP32 rates of 19.5 TFLOPS on A100 and 19.2 TFLOPS on A4000 perform similarly for simulations; choose A4000 for cost, A100 for memory-intensive cases.
Frequently Asked Questions
What is the VRAM capacity of NVIDIA A100 SXM4 80GB versus RTX A4000?▾
NVIDIA A100 SXM4 80GB provides 80 GB HBM2e VRAM, enabling large model handling. RTX A4000 offers 16 GB GDDR6, suitable for smaller workloads. This fivefold difference impacts batch sizes in training.
How do cloud prices compare for these GPUs?▾
A100 SXM4 80GB starts at $0.45 per hour, averaging $1.35 per hour across 27 offers. RTX A4000 begins at $0.08 per hour, averaging $0.37 per hour over 28 offers. A4000 delivers better value for light tasks.
Which GPU has superior FP16 performance?▾
A100 achieves 312 TFLOPS FP16, ideal for accelerated training. RTX A4000 reaches 19.2 TFLOPS FP16, adequate for inference. The gap favors A100 in tensor-heavy AI.
What are the TDP ratings?▾
A100 SXM4 80GB consumes 400W, requiring robust cooling. RTX A4000 uses 140W, enabling efficient multi-GPU setups. Lower TDP reduces operational costs for A4000.
Are both GPUs on Ampere architecture?▾
Yes, A100 launched in 2020 and RTX A4000 in 2021, both Ampere-based. A100 targets datacenters with NVLink; A4000 focuses on PCIe workstations. Compatibility with Ampere software unifies them.
Which is better for LLM training?▾
A100 SXM4 80GB dominates with 80 GB VRAM and 2039 GB/s bandwidth for large models. A4000's 16 GB limits scale. Use A100 for production training.
Which is cheaper to rent, the A100 or the RTX A4000?▾
Cloud rental prices for both the A100 and RTX A4000 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 A4000?▾
The A100 has 40 to 80 GB of HBM2e memory. The RTX A4000 has 16 GB of GDDR6 memory.
Can I find A100 and RTX A4000 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 A4000?▾
The A100 uses the Ampere architecture (2020) while the RTX A4000 uses Ampere (2021). The A100 delivers 16.3x the FP16 throughput and 4.6x the memory bandwidth of the RTX A4000.