OpenClaw Context Budget Calculator
Plan your OpenClaw conversations smarter. Estimate token usage, visualize context window allocation, see when auto-compaction triggers, and understand the budget safeguards — all in real time.
Why Use the Context Budget Calculator
Based on the latest OpenClaw context compaction and token management improvements.
Visual Token Breakdown
See a live stacked bar chart of system prompt, file context, and conversation tokens against your model's context window.
Compaction Trigger Alerts
Know exactly when OpenClaw's auto-compaction kicks in at 85% context usage — and how many turns you have left.
Budget Safeguard Details
Understand the multi-layer caps (900/2,000/16,000 chars) that prevent compaction summaries from bloating your context.
Post-Compaction Preview
See how much context is recovered after compaction — summary tokens, new total, and the resulting usage percentage.
Cost Estimation
Estimate input and output costs per conversation based on real model pricing from OpenRouter.
Turns-to-Compaction Counter
Get a real-time estimate of how many more messages you can send before the context window needs compaction.
Calculate Your Context Budget
Select your model, adjust the sliders, and see your token budget update in real time.
Choose Model
Context window
1.0M
Output limit
32.0k
Input cost/1k
$0.01
Output cost/1k
$0.07
Conversation Parameters
Context Window Usage
Total used
27.0k
Percent used
2.7%
Remaining
973.0k
Est. cost
$2.80
Compaction Status
You have 823.0k tokens remaining before compaction triggers at 85%.
That's approximately 1646 more message turns at your current average.
Compaction Budget Safeguards
OpenClaw enforces multi-layer caps on compaction summaries to prevent oversized context from degrading future turns. These limits were refined in a recent update.
File ops list cap
900 chars
Individual file operation lists truncate with '...and N more'
Combined file ops cap
2,000 chars
All file-ops sections combined cannot exceed this limit
Summary cap
16,000 chars
Final compaction summary hard limit preserving critical trailing sections
Deploy OpenClaw with DeployClaw
Get context compaction, token monitoring, and multi-model support out of the box.
Frequently Asked Questions
What is context compaction in OpenClaw?
Context compaction is OpenClaw's automatic mechanism for managing long conversations. When your token usage reaches approximately 85% of the model's context window, OpenClaw summarizes the earlier conversation history into a condensed representation, freeing up space for new messages while preserving the important context.
Why does compaction trigger at 85% instead of 100%?
The 85% threshold provides a safety buffer. The compaction process itself requires tokens to generate the summary, and the model needs remaining context space for its next response. Triggering early ensures the process completes smoothly without hitting hard limits.
What are the compaction budget safeguards?
OpenClaw enforces three layers of caps on compaction summaries: individual file operation lists are capped at 900 characters, combined file-ops sections at 2,000 characters, and the final summary at 16,000 characters. These prevent any single component from dominating the compacted context. Critical trailing sections like workspace rules are preserved by reserving space within the overall budget.
How accurate are the token estimates?
The calculator provides a useful approximation. Actual token counts depend on exact message content, tokenizer differences between models, and how OpenClaw structures internal context (tool calls, system messages, etc.). Use the estimates for planning and budgeting — not as exact counts.
Does OpenClaw notify me when compaction happens?
Yes. A recent OpenClaw update added user-facing notifications: you'll see a '🧹 Compacting context...' message when compaction starts and a '✅ Context compacted' message when it completes. These work across all channels including Discord, Telegram, and the web UI.
Can I use this calculator for any AI model?
The calculator includes the most popular models supported by OpenClaw via OpenRouter. Context window sizes, output limits, and pricing reflect current OpenRouter rates. If your model isn't listed, choose one with a similar context window size for a useful approximation.