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Outsourcing plus local AI will soon become more economical vs. frontier labs

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Re: Outsourcing plus local AI will soon become more economical vs. frontier labs

#81

Post by cyanydeez »

Chyzwar wrote: post #48

When discussing LLM pricing, people are missing the plot. The subscription token price is 10x-40x cheaper than API pricing. Your 90$ Claude subscriptions give you close to $1000 to $4000 in equivalent API token pricing. The second issue is that the quality of the model “operator” makes a massive difference in the outcomes. Highly skilled senior devs who know how to prompt and have high agency will outperform team peo…

Isn't the plot that it's like an infinite bikeshed but 10% of the biksheds are actually trailer parks and when you finally realize it's a trailer park and not a bike shed you're down 10-100$ because it's token gen is faster than you can actually validate?

Some might say the price wouldn't be great if you could actually process and validate it...

Re: Outsourcing plus local AI will soon become more economical vs. frontier labs

#83

Post by bee_rider »

ecshafer wrote: post #67

I have really been trying to get local models to work. I have tried different harnesses, tooling, skills, prompts, etc. But when I compare claude code with anthropic models or codex with gpt 5.5, vs qwen, glm or gemma and the same harnesses, the frontier models come out massively ahead. I am at the point where I just don't see the point of the non-frontier models, they waste more time than they save.

The hosted frontier models are massively subsidized, right? I think the point of local non-frontier models is just learning at this point, so you’ll be skilled if/when the market starts comparing the actual price of the two different models.

Re: Outsourcing plus local AI will soon become more economical vs. frontier labs

#84

Post by datadrivenangel »

ecshafer wrote: post #67

I have really been trying to get local models to work. I have tried different harnesses, tooling, skills, prompts, etc. But when I compare claude code with anthropic models or codex with gpt 5.5, vs qwen, glm or gemma and the same harnesses, the frontier models come out massively ahead. I am at the point where I just don't see the point of the non-frontier models, they waste more time than they save.

For agentic coding I 100% agree with you, it's worse and slower and more expensive for LARGE coding with local models. Narrow coding (like writing a specific function) is slow but viable. Regular LLM chat usage on high-end consumer hardware is competitive except on cost though. 0

0 - https://www.williamangel.net/blog/2026/05/17/offline-llm-ene...

Re: Outsourcing plus local AI will soon become more economical vs. frontier labs

#85

Post by henry2023 »

ecshafer wrote: post #67

I have really been trying to get local models to work. I have tried different harnesses, tooling, skills, prompts, etc. But when I compare claude code with anthropic models or codex with gpt 5.5, vs qwen, glm or gemma and the same harnesses, the frontier models come out massively ahead. I am at the point where I just don't see the point of the non-frontier models, they waste more time than they save.

local models are 3 to 6 months behind SOTA models with the huge benefit of not needing to send all your IP to a shady third party.

If inference cost comes down (as it has been for the last few years) you’ll be able to run today’s SOTA in your laptop by the end of the year.

Re: Outsourcing plus local AI will soon become more economical vs. frontier labs

#86

Post by bee_rider »

ianhxu wrote: post #26

>frontier models are more capable than the latest from DeepSeek. But is the capability difference enough to justify a 30x price difference? The contradiction here is that without frontier models, there'd be no foundation for models like DeepSeek to reference and catch up to. Is there an economic model that captures this kind of dynamic?

I guess they’d be hoping for very protective IP laws in that case.

Re: Outsourcing plus local AI will soon become more economical vs. frontier labs

#87

Post by kelseyfrog »

Chyzwar wrote: post #48

When discussing LLM pricing, people are missing the plot. The subscription token price is 10x-40x cheaper than API pricing. Your 90$ Claude subscriptions give you close to $1000 to $4000 in equivalent API token pricing. The second issue is that the quality of the model “operator” makes a massive difference in the outcomes. Highly skilled senior devs who know how to prompt and have high agency will outperform team peo…

> The quality of the model “operator” makes a massive difference in the outcomes.

My hunch is that this is the source of much of the variability in outcomes upstream of HN commenters claiming extremes of, "This model changes everything!" to "This[same] model is crap."

We haven't operationalized what it means to "be good at prompting," nor developed proxies/heuristics/shibboleths for accessing prompting skill. There's community skepticism over whether prompting skill even exists. Besides even if prompting skill is real, who wants to hear, "Actually you kinda suck at prompting."

Re: Outsourcing plus local AI will soon become more economical vs. frontier labs

#88

Post by joka88xj »

ecshafer wrote: post #67

I have really been trying to get local models to work. I have tried different harnesses, tooling, skills, prompts, etc. But when I compare claude code with anthropic models or codex with gpt 5.5, vs qwen, glm or gemma and the same harnesses, the frontier models come out massively ahead. I am at the point where I just don't see the point of the non-frontier models, they waste more time than they save.

[dead]

Re: Outsourcing plus local AI will soon become more economical vs. frontier labs

#89

Post by aftbit »

Sebb767 wrote: post #80
aftbit wrote: post #61

Earlier quoted context omitted.

Yes and no. Just take a look at the OpenRouter providers page: https://openrouter.ai/deepseek/deepseek-v4-pro/providers Deepseek v4 Pro is much cheaper when provided by Deepseek itself, likely as a combination of the loss leader strategy you mention and the desire to have more data flow through their pipeline for training. However, the same open weights model, provided by other providers, is somewhere in the $2-3/1M…

> I hope there's always someone willing to make this bet and release better and better open models. What would this bet be? Training is expensive and open weights mean that for hosting you compete on price with people that don't have this item on their bill.

"Attention is all you need" - the larger bet is that by releasing your models open-weight, you'll get more attention and mindshare than if you tried to jump in to compete with the major closed providers, and the value of that attention will outweigh the cost of the training run.

So far, it's really only the Chinese labs (and FAIR or whatever Meta's project is called now) that are doing this. Oh yeah, and Google's Gemma.

At the moment, this is all massively distorted by the prestige and investment money flowing into the space. None of the labs have to charge the real cost of inference let alone the marginal cost of training because they are instead lighting investment money on fire to cover that.

One imagines (though I have not investigated in detail) that there's a degree of national prestige work going on too. The Chinese labs are trying to show that they can build better and more efficient models and are releasing open to undercut the US labs.

Re: Outsourcing plus local AI will soon become more economical vs. frontier labs

#90

Post by mikeocool »

spprashant wrote: post #55
treis wrote: post #28

I think this misses the forest for the trees. Working with ChatGPT is eerily similar to working with offshore Indian devs back in my enterprise days. Productive if guided explicitly but if let run wild there's lots of WTF moments. LLMs are likely to replace outsourced devs because your employees that know the context can use LLMs to do what offshore devs did before.

"offshore Indian devs" are no slouches. They have access to the same GPT models and likely cost a tenth of the median US salary. Businesses are always looking to lower marginal cost. They will hire 1 software architect in US to write specs and 10 software developers in India to babysit 100 agents.

"They will hire 1 software architect in US to write specs and 10 software developers in India" is exactly what everyone said was going to happen in 2004 as software engineering outsourcing really started to gain traction. Malcolm Gladwell's The Earth Is Flat basically made the argument that software engineering in the US was going the way of manufacturing.

And outsourcing certainly became a thing though not in the way everyone predicted. There are far more software engineers in the US today than there were in 2004.

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