DeepSeek v4.1 Flash Is Now Our Best Hacking Model

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/

I have never had looping issues with DeepSeek models. Which provider/serving framework and harness are you using?

Given how fast and cheap DS is, it's just an ideal model with enough "IQ" to let it loose. Another thing they left out of the article, DS becomes really good if you provide custom tools for the task, on it's own it's mediocre.

I love DS flash, it is an amazing workhorse to implement plans created by more robust models (such as GLM). But a more fair comparison would be of DS Flash with GLM Flash.

I have good results with DS4.1 flash because I can iterate faster. I either provide it with correction, or it discovers its failures via the harness. And seems to respond well to empirical evidence rather than go in circles.

So it might need some prodding, but it's likely in this case it was able to brute force after several runs and collecting some evidence.

> . The accepted runs cost $4.65. Failed attempts and replacement runs increased the complete cost to $5.14.

Come on. Lecturing about hubris when your message is damn the consequences, full speed ahead?

If it's a race to build the torment nexus, or a race with a nonzero chance of building the torment nexus by accident, I don't care about winning.

“If we ban CFCs now the Chinese will win!”

“If we ban chemical weapons, nuclear weapons, etc etc our enemies will triumph! They won’t stop!”

“If we switch to biodegradeable plastic then our rivals will have an advantage.”

“If we dont externalize the costs to our population, then they will, and then will win!”

I think workflows can do the job agents do, 20x cheaper and more predictably and safely. They can completely displace agents, just as HFCs displaced CFCs and then we were able to ban CFCs and phase them out through international COOPERATION. The language of COOPERATION is what saves us vs COMPETITION is all about cutting corners and externalizing costs. Google the Montreal Protocol, Geneva Conventions, Nuclear Non Proliferation Treaty, Unleaded Gasoline etc etc.

Agents have got to be marginalized. They are just popular because the labs need to make a ton of money for their investors and recoup their massive spending on training models.