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I had been saying this on HN repeatedly: people are going to use the smartest models for coding. They don't care how cheap your tokens are if they don't have th

I had been saying this on HN repeatedly: people are going to use the smartest models for coding. They don't care how cheap your tokens are if they don't have the highest probability of solving your programming tasks. And I was dead wrong. Now I mostly use DeepSeek Pro myself.

peheje 5mo ago
I mean indsight is 20/20, but saying that is like saying "everyone will just use the best tools". That's not what we see most places in the world for most types of resources.
dcchambers 5mo ago
I think two things happened: 1. The sheer number of tokens that a coding agent can use flipped the math upside down on this equation. If you use the most expensive model for everything those costs quickly become untenable, even for software companies. 2. We realized many of the coding problems we're solving aren't incredibly difficult.
simplyluke 5mo ago
The other thing that's changing is more and more CFOs are looking at the AI spend in engineering departments and hitting the brakes. Token leaderboards were cool when the spend wasn't a double-digit-percent of the entire department's budget including salaries.
weitendorf 5mo ago
I pretty strongly feel the opposite way. Granted I have not used deepseek enough to “know” their model idiosyncrasies as well as Anthropic, so there is a partial skill issue. But I just find it really hard to justify using a less powerful model while I work. The most I’ve ever spent in a month extra on API tokens for my own work is $200, and I pay for the $200/mo Claude. I use these models quite a lot, though not idly (I usually just walk around and do other stuff until I know how im going to approach the next set of problems). So it costs me about $3000/year to get as much as I want of the best model available. Already that seems low enough to not be worth stressing out too much about optimizing it, because it feels like an indisputable good value, and trying to save money with a less powerful model would be optimizing for a $1000-$2000 saving at the expense of a large portion of my work taking longer or being more frustrating and iterative. That’s not a flex or anything, I get that in other countries $3000/yr is a lot of money for a software developer and also a lot of people would perhaps rationally be better off doing X% worse at work or spending Y% more time on tasks to save $Z, if their productivity improvements didn’t translate to more salary. Otherwise if your performance has more upside I really do think that the smartest models are better with the current pricing scheme. Deepseek and the other Chinese models spend a LOT of time thinking, and tend to be much more jagged (benchmaxxed) in performance. How can dealing with that over an entire year be worth $2k? The only situation I can think of where sacrificing my own time/performance to save on inference is batch compute (of course, $1k vs $100k is different from $30 vs $3k) or work where the tier 2 models have crossed the “good enough” threshold. But I think Opus is not even close to that threshold generally yet. As it gets smarter I, and I think most others probably, just try to do harder things faster and hit the next wall.
- jhonof 5mo ago
  I think that's true for now, but eventually there will reach a point where a model is good enough (approaching that right now with frontier models) and there will be diminishing returns. I don't need a PHD level Genius to build me an analytics dashboard for example, so why would I pay for a model with that level of intelligence when I can (eventually) self host a good enough model and run queries for electricity cost + hardware.
  - evilduck 5mo ago
    I think we are approaching that now, with correct expectations. With frontier large models you can often one-shot tasks with vague prompts for stuff like creating CRUD APIs and dashboards around a simple data model since it's such a solved-problem now. With something like Qwen3.6 27B or 35B-A3B and a Strix Halo level computer or a MBP with 32GB or more or RAM, you may need to be more explicit and stay involved and be a little more patient, but you can absolutely get work done with it or delegate tasks to it successfully. My Framework Desktop does a lot of similar work as my Claude subscription at work (Cowork, chats) for 100W of power draw and a little patience waiting for a slow GPU with limited memory bandwidth to crunch the numbers. Agentic coding is obviously weaker but CRUD development and visualization dashboards are within reach, and I'm usually pleasantly surprised at its ability to self-manage devops.
- solenoid0937 5mo ago
  I feel similarly. I'll gladly pay to use the most intelligent model I can find on the best harness I have. Sometimes this is GPT Pro, sometimes this is Opus. I ask AI a lot of questions, not only about code but about my personal life, and I would be willing to pay very large sums to have the best quality output.
- SoftTalker 5mo ago
  You pay $3k/year for personal use? Or out of your own pocket but for your job?
  - weitendorf 5mo ago
jwitthuhn 5mo ago
Yeah I've also found that models are good enough that the extra spend on premium models isn't always worth it, particularly for my small personal toy projects. A $20 claude sub goes a long way when you plan with Opus and execute with Sonnet.
bachmeier 5mo ago
Your comment is a slice of the reasoning underlying the "AI will take all the jobs" claim. I would constantly see references to what AI could do and how fast it was improving. Never a word about cost. We should anticipate that there will always be demand for human labor, for cheap models, for local models, and probably even frontier models.
KronisLV 5mo ago
> And I was dead wrong. Now I mostly use DeepSeek Pro myself. I've wasted over a hundred Euros re-doing work that was done badly due to the model not being up to task (Vue with TS + wrapper components around PrimeVue, needing to handle event and property passthrough and deal with the stupid Vue SFC issues, TS made this much worse than JS would be). I think it was the GLM model through Cerebras Code at the time, in addition to some GPT and Gemini models with the API pricing. That said, DeepSeek V4 Pro is pretty good and I can totally see myself offloading some of the work, as long as a better model reviews the work and provides suggestions/tests for it.
6AA4FD 5mo ago
Props for making a falsifiable claim, noticing it was falsified, and owning up to it.
sergiotapia 5mo ago
You should try Composer 2.5 within cursor. It's so fast, shockingly fast. Going back to gpt/claude is like using dial-up. And it's great for code work. So far nothing has really tripped it up backend, frontend or reporting metabase dashboard stuff. It's nuts.
zuzululu 5mo ago
you weren't wrong your tasks/problems didn't warrant a frontier model and it was always solvable with a cheap chinese model doesn't invalidate the rest of us working on tough problems that demand more expensive models and valuable enough to justify it
vb-8448 5mo ago
> people are going to use the smartest models for coding. They don't care how cheap your tokens are I actually think that's still true and will continue to be true as long as someone else subsidizes the tokens. Once the "free money" runs out, things will get interesting.
- jstummbillig 5mo ago
  Including for DeepSeek you mean.
  - Someone1234 5mo ago
    Yes including for DeepSeek. But while DeepSeek Pro doesn't run on other people's infrastructure, several other Chinese models you get competitors competing to offer them on price. We'll see how it winds up, but we could see models get licensed over half a dozen+ compute vendors, and then you pick your price/offering/features favorite.
culi 5mo ago
DeepSeek pro is frontier at this point.

peheje 5mo ago

I mean indsight is 20/20, but saying that is like saying "everyone will just use the best tools". That's not what we see most places in the world for most types of resources.

dcchambers 5mo ago

I think two things happened: 1. The sheer number of tokens that a coding agent can use flipped the math upside down on this equation. If you use the most expensive model for everything those costs quickly become untenable, even for software companies. 2. We realized many of the coding problems we're solving aren't incredibly difficult.

simplyluke 5mo ago

The other thing that's changing is more and more CFOs are looking at the AI spend in engineering departments and hitting the brakes. Token leaderboards were cool when the spend wasn't a double-digit-percent of the entire department's budget including salaries.

weitendorf 5mo ago

I pretty strongly feel the opposite way. Granted I have not used deepseek enough to “know” their model idiosyncrasies as well as Anthropic, so there is a partial skill issue. But I just find it really hard to justify using a less powerful model while I work. The most I’ve ever spent in a month extra on API tokens for my own work is $200, and I pay for the $200/mo Claude. I use these models quite a lot, though not idly (I usually just walk around and do other stuff until I know how im going to approach the next set of problems). So it costs me about $3000/year to get as much as I want of the best model available. Already that seems low enough to not be worth stressing out too much about optimizing it, because it feels like an indisputable good value, and trying to save money with a less powerful model would be optimizing for a $1000-$2000 saving at the expense of a large portion of my work taking longer or being more frustrating and iterative. That’s not a flex or anything, I get that in other countries $3000/yr is a lot of money for a software developer and also a lot of people would perhaps rationally be better off doing X% worse at work or spending Y% more time on tasks to save $Z, if their productivity improvements didn’t translate to more salary. Otherwise if your performance has more upside I really do think that the smartest models are better with the current pricing scheme. Deepseek and the other Chinese models spend a LOT of time thinking, and tend to be much more jagged (benchmaxxed) in performance. How can dealing with that over an entire year be worth $2k? The only situation I can think of where sacrificing my own time/performance to save on inference is batch compute (of course, $1k vs $100k is different from $30 vs $3k) or work where the tier 2 models have crossed the “good enough” threshold. But I think Opus is not even close to that threshold generally yet. As it gets smarter I, and I think most others probably, just try to do harder things faster and hit the next wall.

jhonof 5mo ago
I think that's true for now, but eventually there will reach a point where a model is good enough (approaching that right now with frontier models) and there will be diminishing returns. I don't need a PHD level Genius to build me an analytics dashboard for example, so why would I pay for a model with that level of intelligence when I can (eventually) self host a good enough model and run queries for electricity cost + hardware.
- evilduck 5mo ago
  I think we are approaching that now, with correct expectations. With frontier large models you can often one-shot tasks with vague prompts for stuff like creating CRUD APIs and dashboards around a simple data model since it's such a solved-problem now. With something like Qwen3.6 27B or 35B-A3B and a Strix Halo level computer or a MBP with 32GB or more or RAM, you may need to be more explicit and stay involved and be a little more patient, but you can absolutely get work done with it or delegate tasks to it successfully. My Framework Desktop does a lot of similar work as my Claude subscription at work (Cowork, chats) for 100W of power draw and a little patience waiting for a slow GPU with limited memory bandwidth to crunch the numbers. Agentic coding is obviously weaker but CRUD development and visualization dashboards are within reach, and I'm usually pleasantly surprised at its ability to self-manage devops.
solenoid0937 5mo ago
I feel similarly. I'll gladly pay to use the most intelligent model I can find on the best harness I have. Sometimes this is GPT Pro, sometimes this is Opus. I ask AI a lot of questions, not only about code but about my personal life, and I would be willing to pay very large sums to have the best quality output.
SoftTalker 5mo ago
You pay $3k/year for personal use? Or out of your own pocket but for your job?
- weitendorf 5mo ago

jwitthuhn 5mo ago

Yeah I've also found that models are good enough that the extra spend on premium models isn't always worth it, particularly for my small personal toy projects. A $20 claude sub goes a long way when you plan with Opus and execute with Sonnet.

bachmeier 5mo ago

Your comment is a slice of the reasoning underlying the "AI will take all the jobs" claim. I would constantly see references to what AI could do and how fast it was improving. Never a word about cost. We should anticipate that there will always be demand for human labor, for cheap models, for local models, and probably even frontier models.

KronisLV 5mo ago

> And I was dead wrong. Now I mostly use DeepSeek Pro myself. I've wasted over a hundred Euros re-doing work that was done badly due to the model not being up to task (Vue with TS + wrapper components around PrimeVue, needing to handle event and property passthrough and deal with the stupid Vue SFC issues, TS made this much worse than JS would be). I think it was the GLM model through Cerebras Code at the time, in addition to some GPT and Gemini models with the API pricing. That said, DeepSeek V4 Pro is pretty good and I can totally see myself offloading some of the work, as long as a better model reviews the work and provides suggestions/tests for it.

6AA4FD 5mo ago

Props for making a falsifiable claim, noticing it was falsified, and owning up to it.

sergiotapia 5mo ago

You should try Composer 2.5 within cursor. It's so fast, shockingly fast. Going back to gpt/claude is like using dial-up. And it's great for code work. So far nothing has really tripped it up backend, frontend or reporting metabase dashboard stuff. It's nuts.

zuzululu 5mo ago

you weren't wrong your tasks/problems didn't warrant a frontier model and it was always solvable with a cheap chinese model doesn't invalidate the rest of us working on tough problems that demand more expensive models and valuable enough to justify it

vb-8448 5mo ago

> people are going to use the smartest models for coding. They don't care how cheap your tokens are I actually think that's still true and will continue to be true as long as someone else subsidizes the tokens. Once the "free money" runs out, things will get interesting.

jstummbillig 5mo ago
Including for DeepSeek you mean.
- Someone1234 5mo ago
  Yes including for DeepSeek. But while DeepSeek Pro doesn't run on other people's infrastructure, several other Chinese models you get competitors competing to offer them on price. We'll see how it winds up, but we could see models get licensed over half a dozen+ compute vendors, and then you pick your price/offering/features favorite.

culi 5mo ago

DeepSeek pro is frontier at this point.