Coding with LLMs in the summer of 2025 – an update

> Gemini 2.5 PRO | Claude Opus 4

Whether it's vibe coding, agentic coding, or copy pasting from the web interface to your editor, it's still sad to see the normalization of private (i.e., paid) LLM models. I like the progress that LLMs introduce and I see them as a powerful tool, but I cannot understand how programmers (whether complete nobodies or popular figures) dont mind adding a strong dependency on a third party in order to keep programming. Programming used to be (and still is, to a large extent) an activity that can be done with open and free tools. I am afraid that in a few years, that will no longer be possible (as in most programmers will be so tied to a paid LLM, that not using them would be like not using an IDE or vim nowadays), since everyone is using private LLMs. The excuse "but you earn six figures, what' $200/month to you?" doesn't really capture the issue here.

The models I can run locally aren't as good yet, and are way more expensive to operate.

Once it becomes economical to run a Claude 4 class model locally you'll see a lot more people doing that.

The closest you can get right now might be Kimi K2 on a pair of 512GB Mac Studios, at a cost of about $20,000.

> Once it becomes economical to run a Claude 4 class model locally you'll see a lot more people doing that.

Historically these sorts of things happened because of Moores law. Moores law is dead. For a while we have scaled on the back of "more cores", and process shrink. It looks like we hit the wall again.

We seem to be near the limit of scaling (physics) we're not seeing a lot in clock (some but not enough), and IPC is flat. We are also having power (density) and cooling (air wont cut it any more) issues.

The requirements to run something like claud 4 local aren't going to make it to house hold consumers any time soon. Simply put the very top end of consumer PC's looks like 10 year old server hardware, and very few people are running that because there isn't a need.

The only way we're going to see better models locally is if there is work (research, engineering) put into it. To be blunt that isnt really happening, because Fb/MS/Google are scaling in the only way they know how. Throw money at it to capture and dominate the market, lock out the innovators from your API and then milk the consumer however you can. Smaller, and local is antithetical to this business model.

Hoping for the innovation that gives you a moat, that makes you the next IBM isnt the best way to run a business.

Based on how often Google cancels projects, based on how often the things Zuck swear are "next" face plant (metaverse) one should not have a lot of hope about AI>

Model efficiency is outpacing Moore's law. That's what DeepSeek V3 was about. It's just we're simultaneously finding ways to use increase model capacity, and that's growing even faster...

> Model efficiency is outpacing Moore's law.

Moores law is dead, has been for along time. There is nothing to outpace.

> That's what DeepSeek V3 was about.

This would be a foundational shift! What problem in complexity theory was solved that the rest of computing missed out on?

Don't get me wrong MOE is very interesting but breaking up one large model into independent chunks isn't a foundational breakthrough its basic architecture. It's 1960's time sharing on unix basics. It's decomposition of your application basics.

All that having been said, there is a ton of room for these sorts of basic, blood and guts engineering ideas to make systems more "portable" and "usable". But a shift in thinking to small, targeted and focused will have to happen. Thats antithetical to everything in one basket throw more compute at it and magically we will get to AGI. That clearly isnt the direction the industry is going... it wont give any one a moat, or market dominance.