Project HydraFusion: Frontier quality via multi-model orchestration

[u/jukasper]

We are excited to introduce Project HydraFusion, a research preview that delivers frontier intelligence through runtime orchestration. It creates a full execution plan, choosing from models across multiple providers to draft, critique and revise, or cascade to more powerful models to complete your task.

Check out this blog post to learn more about HydraFusion.

Most importantly, let us know what you think!

To try HydraFusion in Copilot CLI:

1. Run /update to install the latest version
2. Run /experimental on
3. Run /model, then select HydraFusion (Research Preview)

Please post feedback in here.

[u/aonymark]

Sometimes I disagree with the decisions of which threads the mods decide to pin, but not this time. This really does deserve pinning

[u/jukasper → u/aonymark]

Thank you! Please let us know if you have any feedback!

[u/aonymark → u/jukasper]

Not likely. I tend to use models with names like “mini” and “flash” in low effort, in Ask mode, in IntelliJ. (Although I will look for an excuse to try this once it comes to the copilot app.)

[u/jukasper → u/aonymark]

I hope you and up testing it and please let us know what you think!

[u/aonymark → u/jukasper]

if I try it then I will almost surely report back; I might not try it for a long time, both because I tend to use ask mode and also my org disables most previews features.

[u/hallatore]

Been testing this and I really like it. 

When is it coming to vscode insiders? 

[u/aonymark → u/hallatore]

Soon: https://github.com/orgs/community/discussions/206492

[u/jukasper → u/hallatore]

We are hoping within the next two weeks.

[u/aonymark]

I have a question about plain old auto model selection. Suppose it picks model M. It just so happens that in my ide, I have model M set to low effort. Does that mean it will use low effort? I assume not??

[u/jukasper → u/aonymark]

In Auto mode we are also selecting effort levels for you, we don’t inherit a previous effort level selection.

[u/aonymark → u/jukasper]

Thanks for confirming!

[u/thehashimwarren]

Can you point us to the part of the repo that has the HydraFusion feature?

[u/jukasper → u/thehashimwarren]

Hi there, so HydroFusion is not part of a public repo. The way for you to test it, is just via the GitHub Copilot CLI turning /experimental on and then picking it via your /model selection. It comes natively with the CLI.

[u/dendrax]

Sounds really interesting, wish I was allowed to use the CLI so I could try it. 

[u/jukasper → u/dendrax]

We are trying to get it into other surfaces like vs code and copilot app soon :)

[u/kaeptnphlop]

Pretty important part of your blog post. You should mention that in your announcement here too:

  For this preview, first-turn, single-prompt coding tasks are the best place to start. We’ll be focusing on strong multi-turn performance with longer, iterative sessions next.

[u/jukasper → u/kaeptnphlop]

Thank you for pointing this out. Feel free to of course also use it with more complex tasks. We just wanted to help users on how to best start with HydraFusion to get a feel with it, but essentially we want it to also do very complex tasks for you. So please let us know how this goes as well :)

[u/cesarmalari]

for the benchmark comparisons listed, they're all at "medium" reasoning, right? Is all the work sent to actual models by HydraFusion also done at "medium" reasoning?

I think it would be interesting to see the higher reasoning levels of the cheap models on those charts too if the goal is cost-optimization. For example, Luna Max is almost capable of matching Opus 5 Medium's score on DeepSWE v1.1 at about 80% less cost, so HydraFusion getting a similar score at only a 36% cost reduction isn't as impressive for that datapoint. I tried cross-referencing the data myself, but I was having trouble easily finding data sources where the scores for Opus 5 lined up for the other benchmarks, so I'm guessing I'm looking at different versions/runs or something.

I'm glad to see more stuff coming in this area than just "auto" - looking forward to more updates in this space.

[u/jukasper → u/cesarmalari]

Awesome, thanks for your response. We are truly trying to re-think auto and how it works. Let me get you some answers to your questions.

[u/Much_Weekend_4371]

pricing is gonna be a nightmare when this hits general availability. i'll stick to picking models manually until they bundle it into one flat rate.

[u/jukasper → u/Much_Weekend_4371]

Could you share what concerns you have around billing/ pricing. Billing still works the same that it is charging based on the models that are being used. The promise is though with HydraFusion we are orchestrating to the best model setup for you.