Claude Code Opus 4.7 1M Context Excessive Token Consumption – Rapid Quota Depletion

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

1. 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.
2. Check the Claude Code account, local tool state, and provider configuration involved in the failing workflow.
3. 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

1. Capture the exact error message and the command, editor action, or request that triggered it.
2. Check whether the failure is account/auth, quota/rate, model/provider, local runtime, or deployment configuration.
3. Review the source evidence below and compare it with your environment.
4. Apply one change at a time and rerun the smallest failing action.
5. 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.

Sources checked

• https://github.com/anthropics/claude-code/issues/54770

Evidence note: 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.

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FAQ

What should I check first?

Start with the exact Rapid quota consumption in Claude Code with Opus 4.7 1M context — minutes-scale 90%+ burn from few prompts text and the smallest action that reproduces it.

Can I ignore this error?

No. Treat it as a failed Claude Code workflow until the root cause is understood.

Is this guaranteed to have one fix?

No. The imported evidence supports the troubleshooting path above, but tool behavior can vary by account, plan, version, provider, and local configuration.

How do I know the fix worked?

Rerun the same command, editor action, or request. The fix is working when that action completes without Rapid quota consumption in Claude Code with Opus 4.7 1M context — minutes-scale 90%+ burn from few prompts.