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- I would like to see this (and any model router, frankly) benchmarked against two things, personally:
1) Claude Code's "advisor mode" (nominally, Sonnet 5.5 with a Fable advisor)
2) Copilot's "HydraFusion" model router/advisor combo.
Specifically I would like to see them compared on architecture planning (both human assisted and hands-off with a draft document) and code review, as these are what I have found the most significant improvement on with multi-model systems.
> our initial hypothesis that an ensemble of models can do better than any single model ever could.
To your hypothesis, anecdotally I find both of these offerings to be far superior to any single model for most tasks of any real complexity, and both to have general frustration/failure cases that single models do not. I would not be surprised that any ensemble approach that utilizes more than one single model meets this hypothesis.
Quite frequently I delegate review and restructuring loops to subagents acting as judges/advisors to tell the primary agent if it met the goal it was instructed to. For some workloads, I will even vet every tool call and user-facing output this way.
by devmor - Can it route to locally or LAN hosted Qwen or some other open weights model?by gitowiec
- If you are training on data labeled by frontier models, how do you expect to exceed the performance of frontier models, other than in the cost dimension by recognizing simpler problems and routing to cheaper models?by svnt
- How do you handle provider variance on OpenRouter for the opensource models? Or do you use your own hosted version to mitigate this?
And for both opensource and closed source, does the router account for provider quality, or catch it when a provider degrades?
by ajspig1 - > then there are 10^100 possible paths through that session.
Is this correct? in practice you would only be deciding what the next turn is going to be. Because the turn after the next turn is determined by the outcome of the next turn. So shouldn't this number be 10 * 100?
- That sounds really quite interesting- one question pops up, this sounds like it could produce a lot of non-cache input tokens. How much impact does this have, and are you mitigating it?
Interested in adding support to my own 3code- https://3code.capocasa.dev- which aims to reduce cost by using more compact system prompts and a clever compaction variant.
by capocasa - Interesting work, and thanks for describing how your router works internally. It's definitely a fascinating subject. How would you say this compares to Cursor's auto mode?
- Have you compared this to using GPT-6.1 Sol instead of GPT 6 Astra + Deepseek? From my test, 6.1 Sol is a lot more token efficient than 6 Sol while being similar to Astra in performance, and I don't really find 6 Astra to be significantly better than 6/6.1 Sol for general coding as I feel 6 Astra is only noticeably better at spatial reasoning/vision compared to 6 Sol, and 6.1 Sol really closed the gap on that front.by YuechenLi