u/EchoingAngel

I had a request running when the time ticked and the charging switched immediately for it. In the end, this small, Auto mode request that used GPT 5.3 took 133 of my 7000 credits. so yay, you too can get 50 so-so requests with older models. It changed <200 lines of code and ran for ~1 minute. I'm on Pro+ (until I cancel in T-minus...)

Update: It actually updated to 156 credits used. My subscription ends June 19th.

Update 2: to be unbiased, the next two requests were similar sizes, but came out to ~40 credits each

Hi all, tried digging through past posts and didn't find a clear answer.

The goal is agentic coding with ideally 256k context. The faster the better, ideally without sacrificing quality of reasoning. This will likely be qwen 3.6 27B, and any future comparables.

I'll be doing gamedev work with C# coding, and if local 3D AI modeling is at a good point, a good amount of that. I've been using GHCP with GPT 5.4 for most things and Gemini 3.1 Pro for cleanup work. Obviously I don't expect local to match those, but at a baseline, I'm not using Opus or GPT5.5 anyways.

I have a clean slate for this and would put $5k as the ceiling. I've seen lots of raving about 3090's, but I'm not entirely sure what context window is being achieved. I also am trying to pay some mind to future proofing.

My current computers are a desktop with a 2070 Super and 32GB of RAM and a laptop with a 3060 and 16GB of RAM. I don't expect almost anything LLM-wise from them, except maybe orchestration.

For myself, I began with GPT 4 chat which was very manual and needed tons of handholding. I stayed with OpenAI chat until o1 was removed, then started using GHCP. I mostly used Claude until 4.5 and got tired of how it would give 3x the code than was necessary. I noticed the new GPT's (>5) did the same thing as well; they both were addicted to bloating the codebase.

Due to that, I've been using Gemini since the golden days of free 2.5 Pro API access (privacy concerns aside...). I now use whatever the lightest Gemini model is for most things and hop onto Pro if I need a heavier lift. It isn't AS smart as Claude/GPT, but damn it can make things work with a fraction of the code and token cost.

My take: Anthropic and OpenAI are suckering everyone into making monstrous codebases they know nothing about, so they are dependent on the tools that will then cost even more due to the bloat. That, or the only way they are effective is to output so much, which I see as lesser than Gemini's ability to get more done with less.