I just haven't found them to be very good? I've had a ton more success with the GLM models (since 5.2 anyway). Maybe I'm just holding it wrong, DS models seem to get stuck in loops or tell me nonsense. GLM feels like budget Claude.
It's really crazy. We price per token our customers. If Kimi was about 30% of the price of Opus 5 for the same quality, DeepSeek is 1/10th of a price of Kimi K3. We've come down in price so much that I seriously cannot recommend other models before they reduce their pricing.
And what is really interesting is its programming ability. As I've said in my previous comments, I use agents a lot in my work. Since early Opus days until now I have 7-8 agents working in parallel for different tasks. Rust, design, GEPA, evals, analysis. For a long time Kimi K3 was the best model for this work, and before that GPT 5.5. But I still can't really believe how well DeepSeek works here. I really try to find faults from it, trying to see that it must be doing sloppy work and be worse than the others. But it does not. It finishes every task I give to it. And the cost per task is under a dollar, usually 15-30 cents.
In comparison the same task with Kimi would be 3-15 dollars; sometimes closing to 100. And before that with GPT 5.5 a 800 dollar task was not uncommon if I spent days evaluating models.
Now it's less than a dollar.
For me if the other providers will not drop their prices dramatically in the coming weeks I see no reason to use them. Even with a 200 dollar subscription, paying per token for DeepSeek is better value.
My harness: https://omp.sh/
https://github.com/skorokithakis/amazfit-neo-hacks
Unfortunately, it made a mistake and bricked it. I handed over to Astra but noticed that my watch was dead, it must have died immediately before. Too bad, unlucky me.
I have never had looping issues with DeepSeek models. Which provider/serving framework and harness are you using?