AWS Bedrock上のCodexのバグ、10倍の料金が発生

Uh oh! There was an error while loading. Please reload this page. openai / codex Public Notifications You must be signed in to change notification settings Fork 16.6k Star 109k Native Bedrock Codex GPT-5.6 Sol lacks explicit cache controls, producing high cache-write spend #37674 New issue Copy link New issue Copy link Open Open Native Bedrock Codex GPT-5.6 Sol lacks explicit cache controls, producing high cache-write spend #37674 Copy link Assignees Labels CLI Issues related to the Codex CLI CLI Issues related to the Codex CLI aws-bedrock Issues related to AWS Bedrock provider aws-bedrock Issues related to AWS Bedrock provider enhancement New feature or request enhancement New feature or request rate-limits Issues related to rate limits, quotas, and token usage reporting rate-limits Issues related to rate limits, quotas, and token usage reporting Description apexethdev opened on Aug 9, 2026 Issue body actions Summary Native Codex CLI requests to Amazon Bedrock Mantle cannot opt into GPT-5.6 Sol explicit prompt caching. On an agentic coding workload, this has produced a large volume of cache-write tokens and materially higher cost. This is related to #35300, but adds independent production usage evidence from the native amazon-bedrock provider. Environment Codex CLI: 0.147.0 Provider: native amazon-bedrock Endpoint: Bedrock Mantle Responses API, us-east-1 Model: openai.gpt-5.6-sol Observed production usage For the completed days 2026-08-05 through 2026-08-08, Cost Explorer usage quantities and the Bedrock rate card produced the following cache-aware estimate for Sol: Requests Cache-write tokens Estimated cache-write cost Estimated total cost 3,656 171.94M $1,182.09 $1,386.46 Cache writes were about 85% of the model's estimated spend. A local Codex session also reported 76 Sol requests with 6.709M cache_write_input_tokens, zero cached_input_tokens, and an average of about 88K cache-write tokens per request. There were no client errors in the corresponding CloudWatch metrics. These are usage-derived estimates, not finalized AWS invoice amounts. Investigation Codex already emits a session-scoped prompt_cache_key, but the request types for both HTTP and WebSocket Responses requests do not include either: prompt_cache_options prompt_cache_breakpoint The built-in Amazon Bedrock provider config exposes transport/auth settings, not structured request-body transformation, so this cannot be configured through config.toml. AWS documents explicit cache mode for GPT-5.6 on Bedrock specifically for agentic workflows with long stable instructions/tool definitions followed by changing tool and user content. That matches the workload above. Requested behavior Add support for serializing prompt_cache_options for GPT-5.6-capable Responses providers. Add a typed prompt_cache_breakpoint field to supported input content blocks. Provide a provider/model capability gate and a safe placement strategy at the end of Codex's measured stable instruction/tool prefix. Surface cache reads and cache writes in per-turn usage telemetry so users can diagnose costly full-prefix rewrites. Scope This report does not claim that every cache write is a defect. Cold starts, genuinely distinct prompts, forks, and compaction can all require writes. The issue is that native Bedrock Codex currently has no way to use the documented explicit-cache mechanism for the stable-prefix case. Reactions are currently unavailable Metadata Metadata Assignees celia-oai Labels CLI Issues related to the Codex CLI CLI Issues related to the Codex CLI aws-bedrock Issues related to AWS Bedrock provider aws-bedrock Issues related to AWS Bedrock provider enhancement New feature or request enhancement New feature or request rate-limits Issues related to rate limits, quotas, and token usage reporting rate-limits Issues related to rate limits, quotas, and token usage reporting Type No type Projects No projects Milestone No milestone Relationships None yet Development No branches or pull requests Issue actions Open in GitHub Copilot app