NVIDIA RTX 4000 Ada memory-bound vs compute-bound workloads
💡 Answer
NVIDIA RTX 4000 Ada delivers 107 FP16 TFLOPS and 26.7 FP32 TFLOPS, backed by 360 GB/s of memory bandwidth and 20 GB of VRAM. In mixed-precision fine-tuning, those numbers typically convert to solid throughput on dense models up to several tens of billions of parameters.
For low-latency inference, real-world tokens-per-second on common large language models depends more on memory bandwidth than peak FLOPS — the 360 GB/s figure is the relevant ceiling for autoregressive decoding. On batched workloads like diffusion image generation, compute becomes the dominant factor again.
At $0.76 per hour on the budget-friendly cloud provider, performance-per-dollar is competitive for AI-heavy workloads.
Rent NVIDIA RTX 4000 Ada on DigitalOcean from $0.76/hr — check live availability and deploy.
More FAQs about NVIDIA RTX 4000 Ada
DigitalOcean GPU Provider Review & Key Facts (April 2026)
Snapshot of DigitalOcean: GPU models, pricing, billing granularity, infrastructure, developer tools, support channels, and compliance. Data verified April 2026.
|
DigitalOcean
Simple, scalable GPU cloud for AI/ML
|
|
|---|---|
| Overview | |
| Trustpilot Rating | 4.6 |
| Headquarters | United States |
| Provider Type | N/A |
| Best For | AI training inference fine-tuning LLM deployment LLM serving computer vision startups generative AI research |
| GPU Hardware | |
| GPU Models | RTX 4000 Ada RTX 6000 Ada L40S MI300X H100 SXM H200 |
| Max VRAM (GB) | 192 |
| Max GPUs/Instance | 8 |
| Interconnect | NVLink |
| Pricing | |
| Starting Price ($/hr) | $0.76/hr |
| Billing Granularity | Per-second |
| Spot/Preemptible | No |
| Reserved Discounts | N/A |
| Free Credits | $200 free credit for 60 days |
| Egress Fees | None (included in plan) |
| Storage | 500-720 GiB NVMe boot (included), 5 TiB NVMe scratch on larger configs, Volumes at $0.10/GiB/mo |
| Infrastructure | |
| Regions | New York (NYC2), Toronto (TOR1), Atlanta (ATL1), Richmond (RIC1), Amsterdam (AMS3) |
| Uptime SLA | 99% |
| Developer Experience | |
| Frameworks | PyTorch TensorFlow Jupyter Miniconda CUDA ROCm Hugging Face |
| Docker Support | Yes |
| SSH Access | Yes |
| Jupyter Notebooks | Yes |
| API / CLI | Yes |
| Setup Time | Minutes |
| Kubernetes Support | Yes |
| Business Terms | |
| Min Commitment | None |
| Compliance | SOC 2 Type II SOC 3 HIPAA (with BAA) CSA STAR Level 1 |
DigitalOcean