Could you say more about how caching works? One major advantage of sticking with a single model is saving money on cached input tokens. I'd imagine if you swap between a bunch of models, you may improve performance but cost would would balloon out of control
purplecats•Aug 27, 2026
and caching is related to performance too ofc
SilenN•Aug 27, 2026
The trick is to rarely switch, or switch at task boundaries. Often the conclusion of routing is actually "this one model is actually at the pareto front for this task, just use it always".
cameronh90•Aug 28, 2026
But then it's better to just not have a gateway switch models at all.
Just have the harness able to choose which model its sub-agents use, then tell it how to split up tasks and which models to use when doing so.
SilenN•Aug 28, 2026
That is another way to do. Or we can automatically figure out which models the subagents should be using for you. And update them as new models come out and the work your subagents do changes. More than one way to skin a cat.
ashermania•Aug 27, 2026
Finally an open source tool doing this!
23david•Aug 27, 2026
Super interesting and congrats on the release. Curious if you initially had this in Python and then rewrote in Rust?
SilenN•Aug 27, 2026
Yep! If you look at the commit history that's exactly what happened.
cheema33•Aug 27, 2026
I have not tried it yet. Is it similar to LiteLLM? If so, what sets it apart?
kfallah15•Aug 28, 2026
Router and model optimization from traffic is the main differentiator
SilenN•Aug 28, 2026
Also a hosted marketplace, not just BYOK
ceroxylon•Aug 28, 2026
>The gateway adds under 1 ms for BYOK requests
Amazing! Really brilliant idea, thank you for sharing this project. There is so much ground to cover in the LLM gateway / routing / reporting world, and this is a great start. The Tinker implementation is my favorite part, fine tuning is much better than a sea of context files.
kfallah15•Aug 28, 2026
Thanks! We are going to add continual RL via Tinker soon too
akshay_akula•Aug 28, 2026
Open source and no markup is the right default for a gateway. The caching question above is the one I would want answered before swapping models though.
SilenN•Aug 28, 2026
Ans: we rarely switch, often times it's just a "switch to using this model for your agent"
0xbadcafebee•Aug 28, 2026
You started it a week ago? I look forward to checking back in 3 weeks when you've exited for $1B
SilenN•Aug 28, 2026
See you soon
swthbht•Aug 28, 2026
Very cool. Does your gateway decide effort levels as well? Or just models?
SilenN•Aug 28, 2026
Yep! One interesting example is often Opus 5 on low reasoning ~= Opus 5 on high reasoning.
sangwook•Aug 28, 2026
What online signal recalibrates simulated rankings against actual task success? Also do you have a plan to support semantic caching at the router level?
kfallah15•Aug 28, 2026
For the online signal, we use a LLM judge with a rubric calibrated offline by the user via TUI. UX of the calibration is a major focus area. Semantic caching is interesting, open to supporting it but not currently planned.
forgetme2020•Aug 28, 2026
what's the business model here. How does experiential labs make money
10 Comments
Just have the harness able to choose which model its sub-agents use, then tell it how to split up tasks and which models to use when doing so.
Amazing! Really brilliant idea, thank you for sharing this project. There is so much ground to cover in the LLM gateway / routing / reporting world, and this is a great start. The Tinker implementation is my favorite part, fine tuning is much better than a sea of context files.
Look at the Intelligence features in the Enterprise plan:
* Per-prompt model optimization
* Caching
* A model you own, trained on your traffic