by dabedee on 7/22/25, 9:31 AM
This isn't really about cost savings, it's about control. Self-hosting makes sense when you need data privacy, custom fine-tuning, specialized models, or predictable costs at scale. For most use cases requiring GPT-4o-mini quality, you'll pay more for self-hosting until you reach significant volume.
by tomschwiha on 7/22/25, 9:30 AM
The "not optimized" self hosted deployment is 3x slower and costs 34x the price using the cheapest GPU / a weak model.
I don't see the point in self hosting unless you deploy a gpu in your own datacenter where you really have control. But that costs usually more for most use cases.
by amelius on 7/22/25, 8:17 AM
How to move from one service that is out of your control to another service that is out of your control.
by benterix on 7/22/25, 10:30 AM
To people from Cerebrium: why should I use your services when Runpod is cheaper? I mean, why did you decide to set your prices higher than an established company with significant user base?
by ivape on 7/22/25, 9:53 AM
I’m trying to figure out the cost predictability angle here. It seems like they still have a cost per input/output tokens, so how is it any different? Also, do I have to assume one gpu instance will scale automatically as traffic goes up?
LLM pricing is pretty intense if you’re using anything beyond a 8b model, at least that’s what I’m noticing on OpenRouter. 3-4 calls can approach eating up a $1 with bigger models, and certainly on frontier ones.
by iamlintaoz on 7/22/25, 9:20 AM
Why? Honestly, there are already tons of Model-as-a-Service (MaaS) platforms out there—big names like AWS Bedrock and Azure AI Foundry, plus a bunch of startups like Groq and fireflies.ai. I’m just not seeing what makes Cerebrium stand out from the crowd.
by gordianlabs on 7/22/25, 5:23 PM
Do you forecast costs or just provide more visibility?
by Incipient on 7/22/25, 10:34 AM
Is this article just saying openai is orders of magnitude cheaper than cerebrium?