Please help me understand my Codespaces bill for a 2‑core only workflow

[MatMoto-Admin]

🏷️ Discussion Type

Question

Body

Hi everyone,

I’m trying to reconcile my GitHub Codespaces invoices, and I’d appreciate some help understanding how the charges are calculated.

I used only 2‑core machines. My two invoices show:

Period Days Invoice total
Jan 11–31, 2026 (21 days) 21 days $42.52
Feb 1–28, 2026 (28 days) 28 days $53.27

Given that I only used 2‑core machines, I understand that:

· Compute is billed at $0.18 per hour for a 2‑core machine.
· The multiplier for a 2‑core machine is 2, so 1 active hour on a 2‑core instance consumes 2 core‑hours.
· Storage is billed at $0.07 per GB per month and continues even when a Codespace is stopped.

I have two questions:

1. Can I derive my active compute hours from these totals?
   If my invoice were purely compute, a 2‑core machine at $0.18/hour would imply roughly:
   · January: $42.52 ÷ $0.18 ≈ 236 active hours
   · February: $53.27 ÷ $0.18 ≈ 296 active hours
   These numbers seem high for daily part‑time work, so I must be missing something.
2. How do I separate storage charges from compute charges on my invoice?
   Storage costs $0.07/GB‑month. A 2‑core instance might be to blame for part of the month‑over‑month difference.

My main question:
Given that I used only 2‑core machines, is there a known way to see the exact breakdown of compute hours versus storage on the invoice? Or should I check my usage graph in the billing settings to estimate these numbers?

Thank you for any insights.

[asaddevx]

Hey @MatMoto-Admin — I looked into your invoice numbers. The math you did is actually correct. Here is what is happening.

The invoices combine compute and storage into one line. For January, $42.52 total. Let us break it down.

A 2-core machine costs $0.18 per hour. Each hour uses 2 core-hours because of the multiplier you mentioned . That part is correct.

If you had 4 GB of storage for the whole month of January (31 days), that would cost roughly 4 × $0.07 = $0.28 for storage. But your total is $42.52. That means almost all of it is compute.

236 active hours in January (your math) is actually realistic. That is about 7 to 8 hours per day. If you left your codespace running overnight or over the weekend, those hours add up fast. Even if you were not actively working, the clock keeps running as long as the codespace is active .

Storage does not explain the difference because it is billed per GB per month at $0.07, which is very small compared to compute .

The invoice itself will not show a separate line for compute versus storage. You need to check the usage graph in your billing settings.

Go to Settings → Billing and licensing → Usage → Select Codespaces from the dropdown. That view breaks down exactly how many core-hours you used and how much storage you consumed .

Your math was not wrong. The invoices are just not detailed enough. The usage page will give you the answer you are looking for.

[bvthz5]

Your calculation is close, but the invoice total includes both compute and storage charges, not just active machine hours.

For a 2-core Codespace:

• Compute is charged per active hour
• Storage is charged separately and continues even when the CodeSpace is stopped

So dividing the full invoice only by $0.18/hour will make the active hours look higher than expected.

The best way to see the exact breakdown is in:

• GitHub Billing → Usage → Codespaces

There you can check:

• Compute hours
• Storage usage
• Historical usage graphs and reports

Also, stopped CodeSpaces still use storage until they are deleted, which may explain part of the month-to-month cost difference.

[rozhix]

Your calculation is generally correct, but the invoice includes both compute and storage charges. Storage costs are usually small, so most of the total is likely compute usage — especially if Codespaces were left running for long periods.

The best way to see the exact breakdown is in GitHub Billing → Usage → Codespaces, where you can check compute hours, storage usage, and usage graphs separately.