Pod Spend rate limit problem 5/hr

My account used to have a spending limit of $100 per hour, but one day it suddenly changed to $5 per hour. I submitted a form to request an increase, but after days and days, there was no reply or response. So, I joined their Discord to ask for help. The helper was great and changed my spend rate limit to $80 per hour, but just a few days later, it reverted back to $5 per hour again. I have no idea why and I'm so confused. After a few more days, I received an email asking me to fill out another request increase form. I filled it in and submitted it, but after a few weeks, still no reply at all. I've spent a few thousand dollars on Runpod, and now my account is limited to $5 per hour? please help thank you.
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14 Replies
Dj
Dj6d ago
The $5/hr limit is intentional, and is being set by a human - not a machine. It's being applied because your workloads were affecting the health of the network volume cluster in your region. I was able to raise it before, but the same issue reappeared, so we're reapplied the limit to keep the platform stable for everyone. We'd love to help you scale back up, but we cannot allow you to do this without speaking to our team. I've sent you a message to schedule a call and we can help figure out how to reduce your load on the network volume.
riverfog7
riverfog75d ago
Is there some kind of limit per user like IOPS or throughput for the network volume?
riverfog7
riverfog75d ago
there's no mention of those here
Runpod Documentation
Network volumes - Runpod Documentation
Persistent, portable storage for your AI workloads.
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riverfog7
riverfog75d ago
Hmm or a limit that if exceeded counts as non-fair-usage
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riverfog7
riverfog75d ago
This needs to exist Both for network and network volumes
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riverfog7
riverfog75d ago
Honestly idk Just spun up like 150 pods with different cuda versions and collected data from them
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riverfog7
riverfog75d ago
Its automated
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riverfog7
riverfog75d ago
I just spin up the pod with api with the template and it does testing and collects info, pushes them to s3 then kills itself
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