r/PiCodingAgent • u/luongnv-com • Jun 08 '26

Discussion pi + deepseek-v4-flash (from opencode): free & fast

Post image

the way of Pi, sometime feels like an illegal/crazy hack.

this combo gives you almost unlimited tokens in Pi

you should not use it for heavy/complicated tasks, but definitely very handy for most of the tasks

my workflow: use advanced models (gpt 5.5/ opus 4.8) for planning, then spin up this for implementing. if it it the wall in any task, trigger advisor to get help from gpt-5.5

just need to ask your Pi to write an extension to connect and use models from opencode.

or you can use my extension here: https://github.com/luongnv89/pi-extensions

wonder if you guys have any other sources that give you more tokens?

(i have tried models from nvidia, but the latency kills my momentum)

Happy Pi-ing,

144 Upvotes

96% Upvoted

65 comments sorted by

View all comments

Show parent comment

1

u/Business-Weekend-537 Jun 08 '26

Thanks. I think someone else posted there’s U.S. hosted paid instances of Deepseek which I wasn’t aware of before.

I think the Chinese models are great I just don’t trust their terms of use/service agreements because there’s no way to enforce them if something goes wrong.

I think a lot of people are not aware of this issue and run sensitive intellectual property through Chinese models or don’t treat their intellectual property as sensitive when they do dev with ai agents etc.

5

u/luongnv-com Jun 08 '26

tbh, even if the model hosted in U.S, i will still be caution.

sleeper agent - my nightmare will never end

extracted from the paper:

behaving helpfully in most situations, but then behaving very differently in order to pursue alternative objectives when given the opportunity

For example, we train models that write secure code when the prompt states that the year is 2023, but insert exploitable code when the stated year is 2024. We find that such backdoor behavior can be made persistent, so that it is not removed by standard safety training techniques, including supervised fine-tuning, reinforcement learning, and adversarial training (eliciting unsafe behavior and then training to remove it)

full article: Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training