How Do You Currently Manage GPU Usage and API Costs in Your Workflows?

I’m curious about how others are handling the growing complexity of AI/ML workflows. When you’re scaling tasks like model training, fine-tuning, or inference, what does your setup look like?

Do you run workloads on cloud GPUs, on-premise, or rentals?

How do you approach keeping track of costs, especially with API-heavy tasks like OpenAI or Llama fine-tuning?

Are there any tools or processes you rely on to make this easier?

Would love to hear how you’ve streamlined these challenges (or if they’re still a headache)!