Understanding Token Usage in OpenClaw

Using AI assistants can be costly, especially when it comes to token consumption. Many users are unaware of how their tokens are spent, leading to unexpected bills. The core formula for token usage is:

Token Cost = Context Size × Number of Dialogues

• Larger contexts consume more tokens: This includes uploaded files, conversation history, and tool outputs.
• Each dialogue round sends the entire context to the model, increasing costs with longer conversations.
• Larger models are more expensive: Claude 3.7 > GPT-4o > Kimi K2.5 > Gemini Flash 2.0.

Understanding this can help identify areas for optimization.

Four Ways to Acquire Free Tokens

Method 1: MaxClaw Official Free Quota

MaxClaw, a cloud version based on OpenClaw, offers free tokens upon registration:

• New Users: MiniMax occasionally provides free token quotas for limited use.
• Free Model Access: Users can access free models like Gemini Flash, GLM-4-Flash, and ERINE-Speed, keeping daily consumption between 500,000 to 1,000,000 tokens (approximately $0 cost).
• 15 Free Debugging Rounds: Each user receives 15 free rounds during the MaxClaw testing phase.

How to Access: Register on MaxClaw → Personal Center → Quota Management → Check free token balance and validity.

Method 2: National Supercomputing Internet Platform Activity

In March 2026, the National Supercomputing Internet Platform distributed a large number of free tokens to OpenClaw users:

• 10,000,000 Tokens free quota.
• Additional 30,000,000 API Tokens for platform model calls.
• Validity: Use within two weeks during the activity period.

This is a verified official event, and similar promotions may occur, so keep an eye on updates by visiting national-sc.cn and searching for “OpenClaw token” or “free quota.”

Method 3: Switch to Free Models

This is a stable and replicable strategy for acquiring free tokens. Here are some effective free models:

In January 2026, Kimi K2.5 became the most used model on OpenRouter due to its affordability and strong capabilities.

Configuration: Set defaultModel to a free model in the Gateway configuration file or use slash commands to switch temporarily.

Method 4: Utilize Community Skills in the Skill Store

OpenClaw features a Skill Store where community developers have created tools to optimize token consumption:

TokenOpti-Pro (recommended):

• The most downloaded token optimization skill.
• Automatically cleans up unnecessary records, intelligently caches repeated content, and only transmits necessary information.
• Tested: Processing a 2000-word article reduced consumption from 11,800 tokens to 3,900 tokens, saving about 67%.

Installation: OpenClaw → Skill Store → Search “TokenOpti-Pro” → One-click installation.

Seven Tips to Save 80% on Tokens

Tip 1: Use Slash Commands Effectively

OpenClaw has built-in session compression commands:

• /compact: Compresses the current session, discarding redundant context while retaining core information.
• /reset: Resets the current session context.
• /new: Starts a new session to avoid history accumulation.

Using /compact in contexts of 5,000 to 10,000 tokens can reduce token consumption by 40%-60%.

Tip 2: Divide Tasks Among Multiple Agents

A common mistake is having one agent handle all tasks, leading to mixed memories in the context. Instead, create dedicated agents for each task type:

• One for daily Q&A.
• One for writing articles.
• One for coding tasks.

This keeps each agent’s context independent, significantly reducing total token consumption.

Tip 3: Use Memory Search for Relevant Historical Context

Avoid sending the entire history to the model each time. OpenClaw’s memory mechanism supports semantic search, allowing you to retrieve only relevant historical segments.

Tip 4: Upload Files Instead of Pasting Content

When processing long documents, avoid copying and pasting the entire text, which increases token consumption. Instead, upload files (PDF, Word, TXT) for the AI to read directly, as uploaded content does not count towards dialogue tokens.

Tip 5: Control Context Length

In MaxClaw settings, adjust the “context window size”:

• Use small windows (4K-8K tokens) for simple tasks.
• Use large windows (128K tokens) for complex reasoning tasks.

Choosing the right context size can save a significant number of tokens.

Tip 6: Batch Process Requests

Instead of making multiple requests, consolidate them into one:

• Incorrect: Asking for stock trends one at a time.
• Correct: Requesting trends for multiple stocks in a single inquiry reduces token consumption by about 70%.

Tip 7: Disable Unnecessary Plugins and Tools

Every enabled plugin (like web search, file reading, image generation) contributes to context. Only enable the plugins needed for the current task and disable them afterward.

Comparison of Token Consumption Before and After Optimization

These data come from GitCode community tests in March 2026.

Conclusion

Using AI assistants incurs unavoidable token costs, but it doesn’t have to be excessive. Free models can be used consistently, platform activities can provide additional tokens, and optimization techniques can block up to 80% of waste.

My current approach is:

1. Shift all daily Q&A to free models (Gemini Flash / GLM-4-Flash).
2. Use Kimi K2.5 for writing articles (best value).
3. Start long tasks with a clean session using /new.
4. Install TokenOpti-Pro for automatic optimization.

After a month, my actual paid token consumption has decreased by over 80%.

Managing token bills makes a significant difference.