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Sakana Fugu

sakana.ai

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11–20 of 141 posts

Re: Sakana Fugu

#11

Post by alasano »

ed_mercer wrote: post #3

So basically... openrouter?

OpenRouter Fusion is basically ask N models + synthesizer step.

This is ask a special orchestrator they built, which is in front of a bunch of models, which model would suit the request best.

Regular Fugu seems to be just "pick the best model and route the request there"

Fugu Ultra can generate like a little mini workflow/plan instead to achieve a result

1. Ask GPT to derive the math. 2. Ask Opus to check for implementation/security issues. 3. Ask Gemini to synthesize or resolve disagreement. 4. Return final answer.

I could be wrong but seems to be that at a glance, so I think it's more dynamic than OpenRouter Fusion.

Re: Sakana Fugu

#14

Post by nixosbestos »

AI noob question, is this like Amp? I just use Amp, I ask it to do neat stuff and it does it. I desperately need to invest in my AI skills but every day I open two new tabs and add it to "AI stuff" folder, and then go back to drowning in work to do.

Re: Sakana Fugu

#16

Post by runeblaze »

ed_mercer wrote: post #3

So basically... openrouter?

links to two papers with at least enough apparent quality and novelty to get into ICLR 2026

> So basically... openrouter

:skull:

i now really wonder how many people of the public understood my thesis defense lol

Re: Sakana Fugu

#19

Post by david_shi »

Their research around building a domain specific model is pretty cool, it's kind of like Karpathy's autoresearch but pointed at deciding the optimal model to use at each step of the inference.

If cost becomes an even bigger problem being able to choose "best performance possible" or "strong but cost effective" will be useful.

https://arxiv.org/pdf/2512.04695

Re: Sakana Fugu

#20

Post by prodigycorp »

ngl, I thought sakana.ai was doing cooler stuff than this. that said, the release of a product like this makes sense because it follows your natural intuition when using these models. The best way to use LLMs is to have at least two in your pocket, because the models do a good job at covering each others assets and filling in obvious model-specific blindspots.

it's interesting that they're offering in the form of fixed cost subscription plans too. My impression was that the first party providers can do this because they api inference margins to the tune of 80ish percent. Anyone else orchestrating on top of these models have to pass through these costs or eat it themselves.

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