GPU Cloud Pricing — Compare 40+ Providers in Real-Time

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How to Choose the Right GPU for Your Workload

Selecting the optimal GPU for your machine learning, inference, or rendering workload depends on several key factors: VRAM capacity, compute performance (measured in TFLOPS), memory bandwidth, and of course cost per hour.

For large language model (LLM) training, the NVIDIA H100 SXM5 and B200 SXM offer the highest FP8/FP16 throughput and inter-GPU bandwidth via NVLink. For fine-tuning and smaller models, the A100 80GB remains a proven, cost-effective choice.

For inference workloads, consider the L40S or L4 for their balance of performance and cost. The RTX 4090 is popular for research and light inference workloads at the lowest price points.

Spot instances can reduce costs by 40-70% compared to on-demand pricing. Check our spot price tracker for real-time availability. For predictable workloads, reserved instances from major cloud providers (AWS, GCP, Azure) offer 30-60% discounts with 1-3 year commitments.

Use our comparison tool to see detailed specs side-by-side, or try the training cost calculator to estimate your total costs before committing to a provider.