r/CommandCode • u/FewExplanation5433 • 5d ago

Is it even possible to hit the 5-hour limit using Muse Spark Contributor on GOAT? Because I just did

I’m on the Command Code GOAT plan ($10/mo) and I’ve been running some massive context queries using the Meta Muse Spark 1.2 Contributor model.

According to the math, the rolling 5-hour limit is capped at $14 of usage. Because the Contributor tier is heavily discounted ($0.10/M input, $0.20/M output), a $14 limit should theoretically give you a runway of up to 140 million input tokens.

Well, I was just using plan, and my CLI officially locked me out. I hit the wall.

I wanted to ask the community: Is it actually possible to burn through 140M tokens that quickly just using plan, or is there a glitch in how Command Code calculates the rolling window for the Contributor tier?

I was stuffing a massive codebase into the 1M context window and generating large plans, so the files were huge—but hitting a 140-million token ceiling in under 5 hours seems wild for standard planning workflows.

Has anyone else actually managed to trigger this block on the Contributor model using plan? Did I just feed it an absurd amount of code, or is the rolling limit calculation acting weird for anyone else?

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u/Damiano1905 5d ago

Well the 5 hour limit is 30% I believe and Goat plan gets 20$ worth on that specific model so you have 6$ worth and then you hit the limit.

I was banned when I tried to explain pricing to new users on their discord. 😢

3

u/Straight-War-1323 5d ago

Yeah,you need to consider specific model allowance as well, what I don't understand is, if you use all 20$ of allowance for this specific model, is there still 50$ extra in other models or it counts as using all your credits?

1

u/Damiano1905 5d ago

It was specifically said by the moderator that once you max out your credits on one model you will have used all your credits and will not be able to use them on other models.

1

u/ichisay 5d ago

Ayer hice el 30% semanal en un día con Muse. El 15% mensual, como 60M de tokens de los cuales en caché fueron el 10% solo, así que realmente esto depende de cómo use uno el arnés y para que trabaja con él. Fueron 1100 request aproximadamente