Runpod

“Runpod has allowed us to focus entirely on growth and product development without us having to worry about the GPU infrastructure at all.”

“Surprisingly, the process of migrating to Runpod was extremely easy and seamless.”

“Having partners like Runpod where we can dream those big ideas and know it's going to happen in the way we're presenting it and selling it to our clients is massive for us.,”

“All of these projects, the renders for AMD, the Coca-Cola builds, that has to do with scalability. If we can't scale, we can't deliver. Runpod makes that possible.”

“I'm in a different time zone. I can literally sleep now instead of getting a call at 3AM. It's on Runpod. It doesn't break. It's fine.”

“When you don't need it, you don't run it, and you don't pay for it. That's all gone now.”

“We use a lot of AWS and GCP, but not for GPU or anything related to GPUs. Whenever we touch a GPU, we're not going there. When it comes to GPU, we're using Runpod,”

“We had physical machines traveling for experiences. They break. They need to be repaired. You get a call at 3AM: the computer broke, what are we doing?”

“By leveraging Runpod, we eliminated the infrastructure bottlenecks that slowed us down, and unlocked a cost-effective, high-performance foundation to scale our GenAI platform.”

“We comfortably scaled our workloads 10x without worrying about GPU shortages or excessive costs. That flexibility gave us the headroom to serve enterprise customers with confidence.”

“Runpod’s scalable GPU infrastructure gave us the flexibility we needed to match customer traffic and model complexity, without overpaying for idle resources.”

““Without Runpod, sustaining our business would have been extremely difficult. We truly appreciate it.””

““Runpod gave us a way forward when everything else felt stuck,” one team member reflected. “It’s not just a vendor, it’s part of how we operate.””

““By leveraging Runpod's APIs, we were able to dynamically scale the number of GPU cloud servers according to the live service load,” the team explained. “It allowed us to serve our large-scale infrastructure at nearly half the cost compared to major cloud providers.””

“We didn't seriously evaluate other alternatives before committing to Runpod. We found their approach interesting from the beginning, particularly the ease of integration, and we haven't had a reason to switch since.”

“You guys have genuinely changed the scope of what we've been able to attempt.”

“AWS is very reliable and has everything we need, but it is way more expensive than Runpod. With Runpod, we can choose the right card for the job.”

“I don't totally remember our cost per video back then, but I remember being incredibly relieved that we switched to Runpod. I'd say we likely saved at least 50% on our video generation costs by switching.”

“Runpod is easily one of the most scalable tools that we use in our infrastructure.”

“I believe there is a 15-minute execution time limit for Lambda, which just wasn't flexible enough for what we needed. Even though most of our videos are generated in far less time, we still wanted peace of mind with the flexibility that Runpod's limits offered us.”

“When you go up on the top right and you have how much dollars you're consuming per hour, that's so good because it creates a really nice visibility. It's deterministic and predictable.”

“What's happened is, moving to Runpod, Botto has a better GPU, better graphic models and better resources, but it also costs less. That's something I didn't expect we were going to have.”

“There were services like Runpod that were cheaper and smarter by providing you with the available resources of GPU. We don't need to have a machine 24-hour service for years you can only use for a certain period of time. It felt like a waste of energy, and a waste of money for us.”

““After migration, we were able to cut down our server costs from thousands of dollars per day to only hundreds,” the team said. “Your endpoints can scale down to zero and scale up without a long delay time.””

““We probably spent thousands of dollars per day on SageMaker,” the team shared. “With slow startup times and compute that couldn’t idle efficiently, it became unsustainable.””