Specifications Compared
| Spec | A16 | RTX-4070 |
|---|---|---|
| TDP | 250W | 200W |
| VRAM | 16 GB | 12 GB |
| CUDA Cores | 2,560 | 5,888 |
| Memory Type | GDDR6 | GDDR6X |
| Architecture | Ampere | Ada Lovelace |
| Form Factors | PCIe | PCIe |
| Interconnect | ||
| Tensor Cores | 80 | 184 |
| FP16 Performance | 4.5 TFLOPS | 29.1 TFLOPS |
| FP32 Performance | 4.5 TFLOPS | 29.1 TFLOPS |
| Memory Bandwidth | 231 GB/s | 504 GB/s |
Performance Analysis
Compute performance defines the core disparity: the RTX 4070 Ti SUPER achieves 29.1 TFLOPS in FP16, enabling six times faster tensor operations than the A16's 4.5 TFLOPS for deep learning training. Matching FP32 performance at 29.1 TFLOPS suits scientific computing and simulations, where the A16 trails at 4.5 TFLOPS.
Higher memory bandwidth on the RTX 4070 Ti SUPER, at 504 GB/s, supports larger batch sizes and lower latency in inference compared to the A16's 231 GB/s. This bandwidth advantage sustains throughput for models under 12 GB VRAM, offsetting the A16's 16 GB capacity edge in bandwidth-constrained scenarios.
Efficiency metrics favor the RTX 4070 Ti SUPER: its 200W TDP yields over six times the performance per watt versus the A16's 250W, ideal for scalable cloud deployments.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
A16
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vultr | 8×NVIDIA A16 64GB VRAM | 64GB | 48 vCPU 496GB RAM 1500GB Storage | Singapore | $0.47/GPU/hr $3.77/hr total (8×) | Available | ||
Vultr | 8×NVIDIA A16 64GB VRAM | 64GB | 48 vCPU 496GB RAM 1500GB Storage | Atlanta | $0.47/GPU/hr $3.77/hr total (8×) | Available | ||
Vultr | 8×NVIDIA A16 64GB VRAM | 64GB | 48 vCPU 496GB RAM 1500GB Storage | Bangalore | $0.47/GPU/hr $3.77/hr total (8×) | Available | ||
Vultr | 2×NVIDIA A16 64GB VRAM | 64GB | 12 vCPU 128GB RAM 700GB Storage | Bangalore | $0.47/GPU/hr $0.94/hr total (2×) | Available | ||
Vultr | 4×NVIDIA A16 64GB VRAM | 64GB | 24 vCPU 256GB RAM 1200GB Storage | Atlanta | $0.47/GPU/hr $1.88/hr total (4×) | Available |
RTX 4070 Ti SUPER
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA GeForce RTX 4070 Ti 12GB VRAM | 12GB | 6 vCPU 30GB RAM | 🌍global | $0.50/GPU/hr |
When to Choose the A16
Select the A16 for workloads demanding 16 GB VRAM, such as inference on models exceeding 12 GB that fit within its capacity. Greater availability across 76 cloud offers ensures dependable scaling in PCIe-based multi-GPU configurations for stable, high-memory tasks.
When to Choose the RTX 4070 Ti SUPER
Opt for the RTX 4070 Ti SUPER in performance-critical applications: 29.1 TFLOPS FP16 accelerates training and inference sixfold over the A16. Its starting price of $0.09 per hour and 200W TDP enable cost-effective, power-efficient deployments.
Use Cases
The RTX 4070 Ti SUPER's 29.1 TFLOPS FP16 provides over six times the compute of the A16's 4.5 TFLOPS for faster convergence. Lower average pricing of $0.17 per hour enhances cost efficiency.
RTX 4070 Ti SUPER's 504 GB/s bandwidth supports larger batches with lower latency than the A16's 231 GB/s. Higher 29.1 TFLOPS FP16 ensures quick token generation.
29.1 TFLOPS FP16 on RTX 4070 Ti SUPER accelerates gradient computations sixfold versus A16's 4.5 TFLOPS. Efficient 200W TDP suits iterative cloud runs.
Ada Lovelace architecture with 29.1 TFLOPS FP16 outperforms Ampere's 4.5 TFLOPS for image generation. 504 GB/s bandwidth handles high-resolution textures effectively.
RTX 4070 Ti SUPER's 29.1 TFLOPS FP32 excels in complex simulations, while A16's 16 GB VRAM aids memory-intensive jobs at 4.5 TFLOPS.
Frequently Asked Questions
Which GPU has higher compute performance?▾
The RTX 4070 Ti SUPER leads with 29.1 TFLOPS in FP16 and FP32, compared to the A16's 4.5 TFLOPS in both formats. This sixfold advantage accelerates AI workloads significantly.
What are the VRAM differences?▾
The A16 provides 16 GB GDDR6 VRAM, exceeding the RTX 4070 Ti SUPER's 12 GB GDDR6X. Choose A16 for models over 12 GB, though RTX 4070 Ti SUPER's 504 GB/s bandwidth compensates.
How do cloud prices compare?▾
RTX 4070 Ti SUPER starts at $0.09 per hour, averaging $0.17 per hour across 2 offers. A16 pricing begins at $0.47 per hour, averaging $0.48 per hour over 76 offers.
Which is more power efficient?▾
RTX 4070 Ti SUPER's 200W TDP delivers 29.1 TFLOPS, over six times the performance per watt of A16's 250W and 4.5 TFLOPS. It suits dense server environments.
What architectures do they use?▾
A16 uses Ampere from 2021, while RTX 4070 Ti SUPER employs Ada Lovelace from 2023. Ada offers tensor core improvements for modern ML tasks.
Which handles larger batch sizes better?▾
RTX 4070 Ti SUPER's 504 GB/s bandwidth outperforms A16's 231 GB/s for inference batching. This reduces latency in real-time applications.
Which is cheaper to rent, the A16 or the RTX 4070?▾
Cloud rental prices for both the A16 and RTX 4070 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 A16 have compared to the RTX 4070?▾
The A16 has 16 GB of GDDR6 memory. The RTX 4070 has 12 GB of GDDR6X memory.
Can I find A16 and RTX 4070 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 A16 and the RTX 4070?▾
The A16 uses the Ampere architecture (2021) while the RTX 4070 uses Ada Lovelace (2023). The RTX 4070 delivers 6.5x the FP16 throughput and 2.2x the memory bandwidth of the A16.