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GitHub Copilot code review will start consuming GitHub Actions minutes

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Re: GitHub Copilot code review will start consuming GitHub Actions minutes

#191

Post by briHass »

veidr wrote: post #115

This is funny, but Copilot is still an interesting case-study and (probably) failed predictor of where we are headed. We all know, and have known for a long time, that the AI labs selling dollars for a nickel are going to pull that rug, and up that price, at some point. Copilot, though, has been consistently the weakest mainstream AI coding offering. Inferior to Cursor or Windsurf at editor completions, inferior to C…

If their pricing turns out to be what they claim, and copilot cli has accurate token counts, they had the best deal around.

Just today, when I wasn't being especially chatty with GHCP, I used about 12 requests to get a few thousand line changes in 3 projects I'm juggling. The last project repo of copilot I closed, in 3 hours burned 38M input tokens, 28M cache, and like 400K out. For GPT5.4, high. That's like $135, in half the day, 1 of 3 instances. No crazy tool use, just lots of docs and unorganized code. GHCP charged like 70 cents for that on the old plan.

Re: GitHub Copilot code review will start consuming GitHub Actions minutes

#192

Post by selectodude »

overfeed wrote: post #185
selectodude wrote: post #173

Earlier quoted context omitted.

Some basic math supports it. A GB300 NVL72 is about $6.5 million. Lets say that you need $6 million worth of cooling and another $6 million worth of electricity. At current rates, that's 720 billion tokens worth of Claude Opus 4.7. At 100,000 tokens per second, it pays for itself in about 3 months. Obviously this is an extremely rough calculation. I can even be off by a factor of 10 and it's still a pretty good retur…

Unless you're serving Chinese open-weight models - you have to consoder training costs. If you're off my 10x, then the amortization period is 30 months - far longer than the useful lifetimes of SoTA models. Frontier model development is a Red Queens race: you have to run as fast as you can, just to maintain your position.

The discussion was if Anthropic makes money on inference. They do. They lose billions on training.

Re: GitHub Copilot code review will start consuming GitHub Actions minutes

#193

Post by joshuastuden »

selectodude wrote: post #192
overfeed wrote: post #185

Earlier quoted context omitted.

Unless you're serving Chinese open-weight models - you have to consoder training costs. If you're off my 10x, then the amortization period is 30 months - far longer than the useful lifetimes of SoTA models. Frontier model development is a Red Queens race: you have to run as fast as you can, just to maintain your position.

The discussion was if Anthropic makes money on inference. They do. They lose billions on training.

No, because Anthropic can't serve their models unless they train them.

Training is akin to the cost of building the software/product. Inference is selling the product.

Re: GitHub Copilot code review will start consuming GitHub Actions minutes

#194

Post by joshuastuden »

Aurornis wrote: post #190
Khalos wrote: post #187

Earlier quoted context omitted.

I'm not familiar with that analysis, its accuracy, or its evidence. I would be surprised by this given it seems like providers are still in the growth phase. Typically the burden of proof is on the one making the claim.

https://semianalysis.com/ They have some of the best publicly available analysis on these topics. The full details and numbers are hidden behind the institutional accounts which are priced for investors (not something you sign up for personally) but they're generous with what they send out in their newsletter. If you're not familiar with resources like this I could understand how you'd assume that the providers are h…

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Re: GitHub Copilot code review will start consuming GitHub Actions minutes

#195

Post by pixelpoet »

SchemaLoad wrote: post #176
hacker_homie wrote: post #171

Earlier quoted context omitted.

run local models

You need massively expensive hardware to run them, and they aren't as good. It's pretty clear the base price of AI tools is way higher than we are being charged right now.

I wouldn't call my $2k Strix Halo computer "massively expensive", and it runs e.g. Qwen 3.6 27b brilliantly, with tons of memory to spare and is a full x86 powerhouse pulling 120w at absolute max.

IMO the programming world is far too myopic about / insistent on using laptops, especially macbooks. Just because a crappy deal exists doesn't mean everyone is forced to take it. Local AI is a high performance computing problem and laptops are fundamentally a crappy form factor for it; buy an efficient desktop computer and be surprised at what's possible even with today's crazy prices.

Re: GitHub Copilot code review will start consuming GitHub Actions minutes

#196

Post by BadBadJellyBean »

speedgoose wrote: post #152
malfist wrote: post #145

Earlier quoted context omitted.

> I suspect the API prices are already served at prices with profitable unit economics. There is absolutely no evidence to support this.

We don’t know the models sizes, requirements, and optimisations, but we could take a guess using the infrastructure costs of the largest open weight alternatives that perform slightly worse. In my opinion, it’s a profitable kind of service. They probably don’t pay the public prices for the cloud GPUs though.

Just looking at infra cost is not enough. If the token price doesn't contain all the costs they are losing money and they eventually have to raise prices more.

Re: GitHub Copilot code review will start consuming GitHub Actions minutes

#197

Post by Frieren »

aaarrm wrote: post #124
Frieren wrote: post #36

As financial markets get tighter AI companies will stop subsidizing their services and charge enough money to actually make a profit. It is time to setup local models. It is cheaper, and you already have a computer. Why keep it idle and pay someone else for their CPU?

Won't competition likely keep prices low? At first maybe not, but sooner or later open models will catch up, then it's a completely open market for anyone to host and sell services.

> Won't competition likely keep prices low?

If there are 100 companies you can choose from, yes.

If there are 3 oligarchs that own all options, not.

Capitalism only works when there is competition between many players. When you get less than a dozen players the prices are too easy to increase to maximize profit. They do not need even to talk between them, to not start a price war is the only logical strategy and they follow it. That is why big-tech is so problematic.

In the past, this kind of companies were highly regulated. Phone companies were not allowed to wiretap calls, prices were limited by law, etc. Internet providers had the same regulations applied to them. But service providers run amok without control abusing their position and hurting the rest of the economy. Do not expect lower prices in such unregulated environment.

Re: GitHub Copilot code review will start consuming GitHub Actions minutes

#198

Post by datsci_est_2015 »

lukaslalinsky wrote: post #147
datsci_est_2015 wrote: post #54

Earlier quoted context omitted.

The better your code is architected, the less powerful model you’ll need for it to make sense of it. E.g. a well-designed deployment (infrastructure-as-code) repository doesn’t need a frontier model to be understood well-enough to create a new job / service using sibling jobs / services as templates. And this already saves me dozens of minutes per week, although it’s not a 2x multiplier in my efficiency.

I disagree, even though I'd love for it to be different. With models like Opus, I can give it a good architecture and expect good results. For many of the less expensive models, that is not the case, they make mistakes, you need to over specify, they get stuck in a loop, etc. As you get to the models you can realistically run locally, it gets so frustrating I'd rather be writing the code myself.

At what point will local inference catch up to today’s cloud inference? Will it ever? If it doesn’t, does that imply a certain dead-end for the LLM inference industry?

Re: GitHub Copilot code review will start consuming GitHub Actions minutes

#199

Post by BadBadJellyBean »

joshuastuden wrote: post #193
selectodude wrote: post #192

Earlier quoted context omitted.

The discussion was if Anthropic makes money on inference. They do. They lose billions on training.

No, because Anthropic can't serve their models unless they train them. Training is akin to the cost of building the software/product. Inference is selling the product.

It's quite easy to sell something for a profit if you ignore the costs. Ultimate free money hack. I will start selling canned beans for the price of the beans plus a few cents. I will just ignore the cost of the cans, labor, power, machines, maintenance, distribution, storage and facility space. If I do that the few cents extra are pure profit.

Re: GitHub Copilot code review will start consuming GitHub Actions minutes

#200

Post by Aurornis »

joshuastuden wrote: post #194
Aurornis wrote: post #190

Earlier quoted context omitted.

https://semianalysis.com/ They have some of the best publicly available analysis on these topics. The full details and numbers are hidden behind the institutional accounts which are priced for investors (not something you sign up for personally) but they're generous with what they send out in their newsletter. If you're not familiar with resources like this I could understand how you'd assume that the providers are h…

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If you’re demanding rigorous proof for only one side of an argument while assuming the other side must be true, you’re not interested in honest debate.

The cost of AI inference has been a heavily analyzed topic. I trust the professional analysts much more than the casual Hacker News commenter claiming they’re losing money per token because they’re repeating what they heard some other Hacker News commenter say

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