TuneLLM
Auto Finetuning without any technical hassle.
16 followers
Auto Finetuning without any technical hassle.
16 followers
TuneLLM will bring down your cost by ~10-20x. -> ₹4.4k/day only Just use it like any other API provider, pick a reference model (Fable-5/GPT-5.5 etc) and let our system handle the rest autamatically.
How does the routing actually decide when to use the smaller model versus the reference one, and is there any visibility into the calls being made under the hood?
How does the routing actually work under the hood to hit that 10-20x cost reduction, like are you caching responses, picking cheaper models, or something else entirely? Would love to understand before I trust it for production.
Curious how the cost reduction actually works under the hood - is it routing between models smartly, distilling responses, or something else entirely? And does latency take a noticeable hit compared to going direct to GPT-5.5?
Plugged in my usual prompt stack and the cost line genuinely looked off at first, had to double-check the dashboard. Responses feel snappy too, which I wasn't expecting for that price tier.
Tried TuneLLM on a small coding task yesterday and the response felt surprisingly snappy for the price. Picking a reference model and just letting it route was the easiest setup I have seen in this space.
Swapped in TuneLLM for a side project yesterday and was honestly surprised how painless the switch was, just swapped the base URL and it worked. The cost drop is the real win though, ran a full day of testing for less than a coffee.