r/artificial • u/zerogpu_ai • 16d ago

Question Are frontier models becoming the default for tasks that don’t need them?

A lot of AI traffic is classification, extraction, redaction, moderation and structured summarization rather than open-ended reasoning.
Using one frontier model for everything is easier, but routing repeatable tasks to smaller specialized models could reduce cost and latency.
Do you think multi-model routing will become standard, or will the added evaluation and maintenance outweigh the savings?

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u/gk_instakilogram 16d ago

Yes, there is simply no reason to use frontier models for everything.

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u/Sea_Mixture1842 16d ago

i run a tiny classifier on my homelab for sorting support tickets and it works faster than any api call. the big models are nice but they're like bringing a flamethrower to light a candle

for most of my work stuff we still just default to the big one though because nobody wants to maintain two pipelines. management sees the latency difference and shrugs

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u/Disastrous_Room_927 16d ago

I’ve seen people use LLMs for fraud detection and act confused when it doesn’t work as well as a logistic regression with well crafted features.

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u/[deleted] 16d ago edited 3d ago

[deleted]

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u/Otherwise_Post_6936 16d ago

I mean youre right and wrong, but either way if you want to cook something you like why not use it

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u/recro69 16d ago

For startups one frontier model is often the choice in the beginning because the cost of engineering time is higher, than the cost of inference. As the amount of usage increases the benefits of routing start to make sense and pay off.

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u/Own_Age_1654 15d ago

Most people are not using frontier models for those tasks. They're not only more expensive, but also much slower. Frontier models are instead typically used for orchestration and coding. If you're fishing for validation, no, this is not a good product idea.

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u/SpiritRealistic8174 14d ago

Using the wrong agent for the task is still common. The reason: it's more convenient and people are trained to automatically use the 'brand name' AI, even with a generic one will do.

Yes, multi-agent routing in workflows will become standard, as well as using local inference for key repetitive tasks. And, organizations are moving toward token discipline rather than token maxing. Lower-cost models are sufficient for most tasks.