Comparison of GPU and VPS costs for AI workloads

A comparison of computing options for AI development highlights the cost differences between Virtual Private Servers (VPS) and dedicated GPU rentals. For projects that rely on external APIs, such as OpenAI or ElevenLabs, a low-cost VPS is often sufficient for managing bots and task queues.

However, when running local models that require significant processing power, GPU rental becomes necessary. Hourly rental services like RunPod offer high-end hardware such as the RTX 4090 or A100, which can be cost-effective for short-term tasks like fine-tuning LoRAs or batch processing. Conversely, keeping a high-end GPU running 24/7 is significantly more expensive than using a VPS for lightweight, continuous tasks like hosting databases or Telegram bots.

Individual providers are also offering specialized setups, such as dedicated monthly rentals of an RTX 5060 Ti 16 GB machine for approximately R$ 449, aimed at users seeking to avoid international transaction taxes and high hourly rates.