AI context budget: reserve space before adding input
Reserve output capacity before filling a context window with input. The table allocates 10% of each example window to output and shows the remaining input ceiling.
AI context budget: reserve space before adding input
| Context window (tokens) | Output reserve (tokens) | Input ceiling (tokens) |
|---|---|---|
| 4096 | 410 | 3686 |
| 8192 | 820 | 7372 |
| 16384 | 1639 | 14745 |
| 32768 | 3277 | 29491 |
| 65536 | 6554 | 58982 |
| 131072 | 13108 | 117964 |
| 262144 | 26215 | 235929 |
| 1048576 | 104858 | 943718 |
Formula & method
output reserve = ceil(window × 0.10); input ceiling = window − output reserveWhat can change the answer
Window sizes are hypothetical capacities, not product specifications. System instructions, tool messages and conversation history also consume the budget. Tokenization depends on the model.
Sources & definitions
Method checked:
Continue with a related task
Context Window Budget Calculator
Remaining context equals the supplied context limit minus instruction tokens, history tokens and output reserve. Count all relevant prompt material using your provider’s tokenization rules.
AI Token Cost Calculator
Token cost equals input tokens × input rate ÷ one million plus output tokens × output rate ÷ one million. Enter the rates for your actual provider and processing tier.
Cached Input Cost Calculator
Mixed input cost equals cached tokens at the cache-read rate plus remaining tokens at the uncached rate. A cache hit fraction is an input assumption, not a guaranteed provider behavior.
AI Request Budget Calculator
Affordable whole requests equal budget divided by estimated per-request token cost, rounded down. The calculation assumes the same average input and output usage for each request.