What this error means
Rapid quota consumption in Claude Code with Opus 4.7 1M context — minutes-scale 90%+ burn from few prompts is a Claude Code failure pattern reported for developers trying to fix unexpected extreme token usage/quota exhaustion when using claude code with claude-opus-4-7[1m] model; users want to understand why small turns consume entire weekly quota. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.
Why this happens
GitHub Issue #54770 on anthropics/claude-code opened Apr 29 2026 by eburgagni89. Reproduced 2-for-2 on same project. Labels: area:cost, bug, platform:macos/vscode. Multiple linked duplicates (#54761, #54926, #56075, #58396 €450 consumed). Prompt caching hypothesis — CLAUDE.md + MEMORY.md + skills index rebilled each turn. High commercial value: Max 5x plan users losing hundreds of dollars per session.
Common causes
- GitHub Issue #54770 on anthropics/claude-code opened Apr 29 2026 by eburgagni89. Reproduced 2-for-2 on same project. Labels: area:cost, bug, platform:macos/vscode. Multiple linked duplicates (#54761, #54926, #56075, #58396 €450 consumed). Prompt caching hypothesis — CLAUDE.md + MEMORY.md + skills index rebilled each turn. High commercial value: Max 5x plan users losing hundreds of dollars per session.
Quick fixes
- Confirm the exact error signature matches
Rapid quota consumption in Claude Code with Opus 4.7 1M context — minutes-scale 90%+ burn from few prompts. - Check the Claude Code account, local tool state, and provider configuration involved in the failing workflow.
- Reduce request pressure, check quota or plan limits, and retry with backoff instead of immediate repeated requests.
Platform/tool-specific checks
- Verify the command, editor, extension, or API client that produced the error.
- Compare local settings with CI, deployment, or editor-level settings when the error appears in only one environment.
- Avoid deleting credentials, local model data, or project settings until the failing scope is clear.
Step-by-step troubleshooting
- Capture the exact error message and the command, editor action, or request that triggered it.
- Check whether the failure is account/auth, quota/rate, model/provider, local runtime, or deployment configuration.
- Review the source evidence below and compare it with your environment.
- Apply one change at a time and rerun the smallest failing action.
- Keep the working fix documented for the team or deployment environment.
How to prevent it
- Keep provider/tool configuration documented.
- Record non-secret diagnostics such as tool version, provider name, model name, and command path.
- Add a lightweight check before CI or production workflows depend on the tool.