Is anyone else just exhausted by the pace of all this. The models change constantly and relentlessly and so does the pricing, basically weekly at this point between all the labs.

It feels nearly impossible to have any rigorous approach when choosing a particular model and price point for a task and more like blindly picking one. The time period needed to actually get familiar with various models to a degree you can intuitively choose appropriate ones for a task is moot when it will likely be superseded faster than the needed time.

I guess if companies are footing the bills most employees just opt for whatever the most expensive model they can get away with. Even then choosing between the various leading models is the same kind of frustrating task. Every release every company has the same random collection of graphs and charts claiming the best performance on X, Y, and Z.

You really don’t need to watch it that closely. If the model you’re using today is working well, just stick with it.

If one day you open up Claude Code and it’s Opus 5.1 now instead of Opus 5, no big deal. It probably will work about the same as it did before. Maybe a little better.

Or if you’re on Codex and some new cool Claude model comes out, no worries. There will probably be a similar new model for Codex within a few weeks. Maybe even within a few days.

> The models change constantly and relentlessly and so does the pricing, basically weekly at this point between all the labs.

A dev in my team saw a new model and changed one application to use said model (essentially changing the contents of a url). One week later I received an escalation from the CTO of the company that our pace of weekly usage was in the millions of dollars (rather than low hundred thousands). Turns out that the new model was 5x more expensive but no one noticed.

That's how cutting edge tech has always worked.

Imagine buying a shiny new PC in the 90s only to see it become practically obsolete within a year.

I could see how this might feel frustrating to someone who doesn't enjoy experimenting with new things all the time.

In practice, you can get away without keeping up with everything all the time. For personal use, pick a provider and get on their ~$20/month plan. Learn their high/medium/low model hierarchy. Start with their highest or second-highest model (GPT-5.6, Opus, etc) and observe your quota usage. If you're doing a lot of manual code review and analysis, the $20/month plan goes very far even on the highest models. If you're trying to vibecode everything as fast as possible it's a different story.

If you keep running into quota limits, experiment with the next model down for easier tasks or adjusting the effort level. If the results are good enough, you've found your fit. If they're not, you might need the next plan up.

For API/business use, you have to be checking your token spend as you go to calibrate to how much each task costs and where you fall in your budget. There are a lot of different tools that make this easy to visualize.

For data tasks, you should have an eval with a golden dataset that you can run against new models for a nominal amount of token expenditure. It should be as simple as pointing the eval script at a new API or model and checking the score versus price.

The new releases and breakthroughs do the opposite for me - I feel energised by them. I felt like nothing truly that interesting had happened in tech for quite some time, now it's like the space race (except there is no one moon to reach).

I appreciate boring tech as much as the next well worn engineer and I'm not saying this is all positive but it's so sure as hell thrilling and you don't have to be an astronaut to immediately benefit (or suffer I guess) from it.

Hey, I'm on the team at LiteLLM that's building the auto-router and our goal right now is to abstract that decision making away from the end user. The biggest thing we're trying to figure out right now is how do we do that without frustrating the end user - as a developer myself I would hate for my agent to be dumbed down below the threshold needed to complete a task.

In theory though, there is a minimum viable model for any given task, and we think that is a problem that the big labs will avoid because they profit from charging more per task. We're trying heuristic and LLM-based approaches but it's still a work in progress, so if this is something you'd be interested in trying would highly recommend trying ours out -- any and all feedback at this point is extremely valuable to us.

https://docs.litellm.ai/docs/proxy/auto_routing

Fire and motion, Joel Spolsky blogged about this:

https://www.joelonsoftware.com/2002/01/06/fire-and-motion/

It feels like this every day

https://youtube.com/shorts/vGKC9LpGnOQ?is=iCG7qvAIL9oI5-_d

It is exhausting to keep up with model releases yes, much like it was for a while during the Cambrian explosion of FE frameworks, eventually tech seems to work out to consolidation.

But more so it seems there is Fear of missing out (FOMO) in our behaviours. The reality is, if whatever model you are using are good for your purpose, well, keep on it.

  > Is anyone else just exhausted by the pace of all this.

Yeah I'm a bit exhausted at this point. I just finished benchmarking GPT 5.6 Sol and Fable 5.0 like two days ago. My data became obsolete literally one day after.

I stopped caring about the latest and greatest but because there's so much, the 'obsolete' free models do what I need and are worth the price.

I want the cheapest fastest model personally and at work. Stay in flow, edit like the wind.

maybe thats why opnrouter sold big

If model X fits your need, you don't need to upgrade.

I have released applications on Gemini 3.5 flash that make real money and I don't see any particular reason to upgrade.

I just use Claude Opus and the GLM series. Nothing’s really changed for my workflow in the last 6 months.