NVIDIA A2 vs NVIDIA L4 — GPU Comparison (Apr 2026)
NVIDIA A2 (16GB GDDR6, 18 TFLOPS FP16, Ampere) vs NVIDIA L4 (24GB GDDR6, 121 TFLOPS FP16, Ada Lovelace). Cloud pricing: NVIDIA A2 from $0.22/hr, NVIDIA L4 from $0.39/hr. Compare specs, VRAM, performance, and pricing across 2 cloud providers to find the best GPU for your AI workload.
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NVIDIA A2
16GB GDDR6 · Ampere
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NVIDIA L4
24GB GDDR6 · Ada Lovelace
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|---|---|---|---|
| Specifications | |||
| Manufacturer | NVIDIA | NVIDIA | |
| Architecture | Ampere | Ada Lovelace | |
| VRAM | 16 GB GDDR6 | 24 GB GDDR6 | |
| Memory Bandwidth | 200 GB/s | 300 GB/s | |
| FP16 (Tensor) | 18.0 TFLOPS | 121.0 TFLOPS | |
| FP32 | 4.5 TFLOPS | 30.3 TFLOPS | |
| TDP | 60W | 72W | |
| Release Year | 2021 | 2023 | |
| Segment | Data center | Data center | |
| Best For | Edge inference entry-level AI | Inference video transcoding lightweight AI workloads | |
| Cloud Pricing | |||
| Cheapest On-Demand | $0.22/hr | $0.39/hr | |
| Cheapest Spot | — | — | |
| Providers | 1 | 1 | |
| Provider Pricing (On-Demand) | |||
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$0.22/hr | N/A | |
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N/A | $0.39/hr | |
NVIDIA A2
NVIDIA L4
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Cherry Servers vs RunPod - GPU Provider Comparison (April 2026)
Head-to-head comparison of Cherry Servers and RunPod. Compare GPU models, hourly pricing, billing granularity, spot instances, VRAM, infrastructure, developer tools, Kubernetes support, and compliance before choosing a provider. Data refreshed April 2026.
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Cherry Servers
Bare metal GPU servers with 24 years of hosting experience and full hardware-level control.
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RunPod
The cloud built for AI — deploy and scale GPU workloads from serverless inference to instant multi-node clusters on demand.
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|---|---|---|
| Overview | ||
| Trustpilot Rating | 4.6 | 3.7 |
| Headquarters | Lithuania | United States |
| Provider Type | N/A | GPU-Focused |
| Best For | AI training inference fine-tuning rendering research HPC generative AI deep learning | AI training inference fine-tuning Stable Diffusion batch processing rendering research LLM serving generative AI |
| GPU Hardware | ||
| GPU Models | A100 A40 A16 A10 A2 Tesla P4 | B300 B200 H200 H100 SXM H100 PCIe H100 NVL MI300X A100 SXM A100 PCIe RTX 5090 RTX PRO 6000 L40S L40 RTX 6000 Ada RTX 5000 Ada RTX A6000 RTX A5000 RTX 4090 RTX 4080 SUPER RTX 4080 RTX 4070 Ti RTX 3090 Ti RTX 3090 RTX 3080 Ti RTX 3080 RTX 3070 A40 A30 A2 L4 |
| Max VRAM (GB) | 80 | 288 |
| Max GPUs/Instance | 2 | 8 |
| Interconnect | PCIe | NVLink |
| Pricing | ||
| Starting Price ($/hr) | $0.16/hr | $0.06/hr |
| Billing Granularity | Per-hour | Per-second |
| Spot/Preemptible | No | Yes |
| Reserved Discounts | N/A | 15-29% (1-month to 1-year plans) |
| Free Credits | None | $5-$500 bonus after first $10 spend |
| Egress Fees | N/A | None (Free) |
| Storage | NVMe SSD, Elastic Block Storage ($0.071/GB/mo) | Container/Volume ($0.10/GB/mo), Idle Volume ($0.20/GB/mo), Network Storage ($0.07/GB/mo 1TB) |
| Infrastructure | ||
| Regions | Lithuania, Netherlands, Germany, Sweden, US, Singapore (6 locations) | 31 global regions |
| Uptime SLA | 99.97% | 99.99% |
| Developer Experience | ||
| Frameworks | PyTorch TensorFlow CUDA (bare metal — full stack control) | PyTorch TensorFlow JAX ONNX CUDA |
| Docker Support | Yes | Yes |
| SSH Access | Yes | Yes |
| Jupyter Notebooks | No | Yes |
| API / CLI | Yes | Yes |
| Setup Time | Minutes | Instant |
| Kubernetes Support | Yes | No |
| Business Terms | ||
| Min Commitment | None | None |
| Compliance | ISO 27001 ISO 20000-1 GDPR PCI DSS | SOC 2 Type II |
Cherry Servers
RunPod
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