This plugin uses sqlx underneath which handles prepared statement caching. Regarding migration, we just used a coding agent to migrate our database infrastructure to it. It takes <20 minutes and remember this really only helps with static queries. We do support sqlc's dynamic queries though.
Tip: you can use case statements and etc. to create static queries even when you have conditionals.
We are aware of this. There was a bug that overcounted and now it's been fixed. If you'd like for us to delete your account, please contact [email protected].
First, thanks for signing up early. It means a lot.
The $10/mo price needed 465 people to fill a cohort before we could turn on a single GPU. People signed up and churned while waiting, so we looked at the reservation pattern and determined 80 slots was optimal. This reflects in the new price and throughput.
We're considering a 1-week option so people can test it out before committing to a full month. Would that help?
The audience here is developers buying API access. They want to see the model, the price, and the throughput, not a hero image and three paragraphs about our mission. Marketing copy between a developer and that information is friction.
You're right that we're less flexible than OpenRouter or Chutes. We don't let you hop between models per-request. If you want that, use those. If you want predictable cost and guaranteed throughput on one model, that's us.
On TEE: yeah, it's stronger, but it also adds cost and latency. We run dedicated hardware with no prompt logging and an isolated proxy. For most people who just don't want their data in someone's training set, that's enough. If your threat model is more serious than that, we're not the right choice.
On models: we are focusing on Qwen for now. We add based on demand. Would you actually use MiMo-V2-Pro or Trinity if we had them?
Thanks to everyone who shared feedback. We’re implementing it now.
Here’s what’s changed:
- We’ve removed the other LLMs for now and are focusing entirely on Qwen 3.5. We’ll bring back additional smaller models later, but most usage was already concentrated on Qwen 3.5.
- Pricing is now around $50. You get roughly 2× the throughput (61 tok/s vs. 31 tok/s, verified in testing), and it’s still unlimited. For context, that’s about 158M tokens per month. Comparable providers like Novita charge around $3.2 per million tokens, so this comes out to roughly 10% of typical token costs.
- Context size is now capped at 32K tokens. For the vast majority of use cases, this is more than sufficient.
Going on ChatGPT.com and using their AI for 24 hours doesn't mean you are actually using their LLM for 24 hours. It's only live for as long as the output is being generated. You reading, waiting for tool calls, etc. don't count toward concurrency. Factor in time-zones, lunch times, etc...it's more likely that we'd have an underutilization problem.
For filling up the cohorts, I agree and we're launching for a week to gather feedback.
No cohorts have been filled yet. We're still early. We are seeing reservations pick up quickly, but I'd be able to give you a more concrete estimate of fill velocity after about a week.
That said, we're planning to add a 7-day window: if a cohort doesn't fill within 7 days of your reservation, it cancels automatically and your card is released. We don't want anyone's payment method sitting in limbo indefinitely.
Tip: you can use case statements and etc. to create static queries even when you have conditionals.
Also, read https://news.ycombinator.com/newsguidelines.html#generated