Yesterday i was testing Vertex AI fine tuning with using text-bison model a 3KB file (10 examples total). The first try took about 3 hours and failed at the end while creating an endpoint, the very last step.
I tried it agiain with Compute Engine API service account another time which took around 2,3 hours and succeded. This was also with the same .jsonl file of 3 KB in size.
When i check this morning i have noticed that i was charged $254 for this.
I would like to know why? How is this possbile?
Considering I ll have 14000+ examples on my original data, i would like to know more about htis pricing becuase this does being stated anywhere…
Most expensive option. The hourly cost can range significantly depending on the region, but it’s generally considered the premium choice for heavy-duty workloads.
Example: In the us-central1 region, the cost could be around $3 per hour or more.
TPU 64 Core v3 Pod
Significantly more cost-effective than A100 GPUs. TPUs are designed to offer better price-to-performance for certain machine learning workflows.
Complexity: Pricing for TPUs is sometimes listed per pod (which contains multiple TPU chips), making direct hourly comparisons tricky.
Example: In the us-central1 region, a v3-8 TPU (which is a smaller unit) costs around $1 per hour. A full pod would likely be proportionally more but still significantly less expensive than a comparable time on the A100.
(Provided by Gemini)
Yet this still does NOT explain why 10 examples took 3 hours adn costs above $200.
