[Bug report / diagnostics]: Native Responses pre-output latency persists in 2.76/2.77 A/B; need supported stage attribution and recovery guidance #6568

Client or integration

Codex CLI

Area

Proxy and routing

Summary

Native Codex requests on Windows show materially longer pre-output waits while output delivery after the first visible delta is broadly unchanged. The installation is usable, but latency and intermittent pre-header connection failures remain unresolved. Expected: prompt request delivery, clear stage attribution, and a supported recovery path for the observed failures.

This is a field report asking for supported diagnosis, not a claim that OpenCodex is uniquely responsible. Existing observations do not isolate provider queueing, prefill, network upload/handshake, and all proxy/client behavior. Separate issue #6567 covers mixed historical tok/s formulas; correcting that display must not count as repairing this latency.

Reproduction

1. Use the official Codex CLI through the installed native OpenCodex Responses route and existing ChatGPT login.
2. Run codex exec --ephemeral --skip-git-repo-check --sandbox read-only --json --color never -m gpt-6.1-sol -c model_reasoning_effort=\"medium\" - from an empty directory.
3. Provide a harmless fixed prompt instructing it not to use tools and to repeat The quick brown fox jumps over the lazy dog. exactly 12 times, one line each.
4. Correlate completion events with the local request log. Each compared request had one physical send, no replay, the same model/effort and default service tier.
5. Compare a short controlled 2.77 → 2.76 → 2.77 sequence with production configuration and selected account unchanged. The retained 2.77 installation was restored after the trial.

Observed first visible output / request duration, milliseconds:

Input was approximately 17.3k tokens; output 135–143 tokens including 9–17 reasoning tokens. Cache hits varied. The small sequential sample cannot establish or exclude a version-level latency cause; it shows that reverting versions did not consistently remove the wait.

Version

OpenCodex 2.77.0, controlled comparison with 2.76.0. Bun 1.4.0. Official Codex CLI 0.160.0.

Operating system

Windows 11 x64; exact Windows feature-update version was not included in this report.

Provider and model

Native OpenAI Codex Responses, GPT-6.1 Sol, medium reasoning, default service tier. Same existing account selection policy and serving account across the correlated test requests. Outbound HTTP proxy in use; no VPN node or account was switched for the version comparison.

Logs or error output

A temporary loopback observer forwarded only these diagnostic requests/responses unchanged to the existing OpenCodex service and retained scalar timing, not authentication, request bodies or response text. Two samples with the same 83,938-byte client request yielded:

Upstream timestamps have whole-second precision. Their difference corroborates a substantial response lifetime but does not identify the backend phase. Completed WS attempt records have requestBytes: null, limiting upload-stage attribution.

Real failures include:

Provider connect timeout after 200000ms
upstream_reset_replay_refused
codex websocket closed before a Responses terminal event (no-upstream-frame)

A later 15:17 UTC+08:00 observation, already posted in the comments, also contains repeated upstream Our servers are currently overloaded. Please try again later. responses. This does not establish a service-wide outage or prove that all slow requests share one cause.

Screenshots and supporting files

Only redacted scalar results are included. Raw logs, account identifiers, private prompts, request/conversation identifiers and business data are not attached.

Broader observational windows on 2026-10-04: 09:00–10:00 local time had 905 successful medium requests, median first visible output 5435.5 ms. Later natural windows were slower, including about 20 seconds following a machine restart. Consistent visible-token/window estimates remained around 33–34 tok/s. Same-conversation examples with fewer input tokens were also slower, so context growth alone is not established as the explanation. These windows are not identical-input experiments.

The native WS pool/session/exchange/request files compared unchanged between official 2.76 and 2.77 archives. Twelve offline same-input request-build tests produced equal destinations, headers, bodies and WS frames; this is not coverage of the entire live pipeline.

Two local compatibility changes were retained and disclosed: known-native unsupported legacy minimal effort normalization, and use of the existing 250 ms bounded reader for optional Windows catalog advice. Ordinary medium requests are not downgraded; unknown/stale advice remains suppressed. The bounded advice change reduces a known local advisory wait but does not eliminate this latency.

Redacted configuration

Native Responses route; provider request pacing off; no forced-off upstream WebSocket override; official default 200000 ms connect deadline. The client-facing WebSocket setting was not treated as the upstream setting.

A temporary forced-HTTP override previously caused a distinct slowdown and was removed. Normal successful requests again have real upstream WS and connection-reuse evidence. No global Fast, model/effort downgrade, account rotation, retry-safety override, unknown-result replay or private credential extraction was used.

Requested guidance:

1. Which supported diagnostic separates upload/upgrade, upstream accepted-to-generation, and local relay delay without capturing user content or credentials?
2. Is a known compatibility or routing regression consistent with these measurements? Please identify a supported mitigation or next minimal falsifiable test rather than treating HTTP 200 as latency acceptance.
3. Can completed WS attempts preserve the actual sent-byte count and bounded stage timing instead of requestBytes: null?
4. If attribution lies outside OpenCodex, what upstream escalation and minimal private diagnostic fields are supported?

Checks

• I searched existing issues and documentation.
• I removed secrets, tokens, account details, request credentials, and personal data.