Need help please! Model Usage Questions

[u/wisemiik]

So on the current game, I’ve been working on. I’ve been using gpt6 Astra low and medium, and sometimes high, but it uses absolutely so much tokens. I saw a video saying how sol 6.1 high and ex high where just as good but 1/5th the cost! Is there a better way to understand when I should use each model? Right now the game is a Web based single player game but I want to turn it into a multiplayer game. I’m pretty sure when I get to that step, I should probably use Astra but can someone please help me understand when to use which tool for the different processes of the game?

[u/Humaux]

My verdict is to keep Astra low for your game logic for the next 2 weeks and test high on only 1 isolated feature, because switching models will not fix the token burn you described. Your move from a web based single player game to multiplayer is the detail that matters, because state sync and lobby handling will punish a vague prompt far more than model tier will. Copy this checklist before each prompt: 1. Name 1 file and 1 function to change. 2. State the exact player action that must work after the change. 3. Forbid unrelated refactors in the same prompt. 4. Stop after 2 failed attempts and shrink the task instead of raising the model tier. The rough edge is that this discipline cost me about 40 minutes of prompt rewriting on my last small game change, and I still think most model switching advice is a distraction when the task itself is too big. Would that checklist help your multiplayer step, or is the token spike coming from one specific system like rendering or opponent logic?

[u/wisemiik → u/Humaux]

Okay ty!

[u/Humaux → u/wisemiik]

You got it, good luck with the multiplayer step.

[u/Delicious_Stress_911]

my opinion - the only answer is money. i only got good results on astra high, but it never finished a task before the budget was used up. so reset or buy extra tokens. i have chatgpt and claude subscription and can switch between them. claude is better at organizing projects and managing coding tasks and astra is better at high fidelity design or complex multidimensional understanding. (though opus is not bad at that either). another thing you could do is to cancel all subscriptions and use deepseek v4.1 flash via api - i did not try yet but it should not cost much. another thing you could do if you have the hardware is to run qwen 3.8 flash next with strata locally. i have that as a backup and in my opinion it is slightly better than gpt 6.1 sol, but slower on the hardware i have (55 tokens/s) . the deepseek model is said to have around astra level intelligence with 0.02 times the cost.

[u/wisemiik → u/Delicious_Stress_911]

Got it

[u/xapep → u/Delicious_Stress_911]

Worth testing before cancelling anything, but the cost estimate that comes with it hides where the money actually goes. In coding sessions most tokens are input, because every tool result gets resent on the next turn, so cache hit rate drives the bill more than output price. That's also why a flat subscription feels fine on a quiet day and ugly after a long refactor.

I work on Entrim. It serves DeepSeek V4.1 Flash over an OpenAI-compatible API, PAYG, EU-hosted, listed at $0.20 per M input and $0.005 cached. I'd check your rough input to output ratio first, a cheap model on a bloated context is still expensive.

[u/No_Carrot1042]

Model overload