I use both the openai subscription and the opencode go subscription. I use the go subscription for my personal work and the openai subscription for my consulting work.
The differences between the models are minimal, but I usually stick with gpt-5.4-mini, gpt-5.4, mimo-pro-2.5, deepseek-v4-pro. These latter ones have way more usage than even using 5.4-mini so I tend to use them in personal projects for that reason.
Thanks.
I was looking at open code go yesterday and I couldn't figure out if the base pricing is including usage or if that's just base pricing and then you have to pay for usage too. How does it work? It is very cheap.
OpenCode Go is a smoking deal IMO. You basically get 6x multiplier on the $10 price since you get $60 worth of usage for $10. And the first month is only $5 so it's even better.
It goes pretty quick, but it's still a great deal. Highly recommended.
"Death of Silicon Valley" in this case is such a funny perspective. Like, how twisted is the US's view of the market that they think "Competition? Oh no. Sound the alarms."
Except it’s not competition if US companies can’t access the Chinese market but Chinese companies can access the US market. Just like cars. America is not willing to compete with BYD. But we are 20 years into massive IP theft from China and the naive and short sided leadership in the US that basically traded our knowledge, design and manufacturing knowledge for cheap of shoring, and watch China execute spectacularly to take advantage of the opportunity.
It's the only model where an explicit instruction at the end of my message is sometimes ignored. This doesn't happen with any of the gpts, kimis, glms, qwen, etc. Just a deepseek problem.
I have also noticed this with Sonnet, funnily enough - it's not as strong, but it's still there. But yeah, I haven't seen this with any other model so far (although I mostly use the stronger ones - maybe it's a function of intelligence?).
Have you tried DeepSeek V4 Flash? It's very competent and extremely cheap.
I think Gemma 4 is also a good example of a capable small model.
I mention these not only because they're cheap but because they can run on consumer devices. The "every year bigger and more capable SOTA model" trend is mirrored by "the every year smaller and more capable open source model" trend.
256GB is what deepseek v4 flash with Q4 requires I believe. It is really still very far from “running locally on your device”. And it’s getting further away every day, looking at how the electronic market prices are surging.
I need to find stats on average RAM of personal devices, but I expect it will be so low, we are light years away from running a frontier model (from today) locally on a smartphone, let’s stop dreaming (and I really would love having it).
I do agree local models are progressing and I am to this day in awe at what a 50GB file can do – it still feels like black magic to me.
Also granted, something like Gemma 2 2B seems to have similar performance to ChatGP 3.5 and only require 2GB of RAM. But I think the RAM/performance ratio curve over time is logarithmic and not linear, it’s moving slower and slower.
I use it through my opencode go subscription and it's exactly how you described. Very pragmatic and not too ambitious. It's similar to Kimi 2.5/6 in that regard.
But...AWS is a platform too, no? Seems like you're in the same category of risk you just moved to a more well-known name. Granted, Amazon is the most reliable even if they have their own quirks.
I was looking at this from Railway’s perspective. I really wonder what caused their account to be flagged, and they hint at more accounts being erroneously flagged as well.
Showdead is quite a disheartening experience - there’s just so much LLM generated crap. The dead internet theory doesn’t feel as fringe as it once did.
The differences between the models are minimal, but I usually stick with gpt-5.4-mini, gpt-5.4, mimo-pro-2.5, deepseek-v4-pro. These latter ones have way more usage than even using 5.4-mini so I tend to use them in personal projects for that reason.
My harness is https://github.com/can1357/oh-my-pi. I trust it...enough. It updates very frequently so as a safe guard I run it sandboxed with https://github.com/containers/bubblewrap so it can only access the project folder and some whitelisted config files
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