Is there a workaround for OpenClaw Codex latency?

Using PI (personal intelligence) mode remains faster and more usable for interactive OpenClaw chat, even though it still carries a large prompt.

Why is OpenClaw Codex runtime so slow?

OpenClaw injects approximately 30K tokens of tool, channel, and workspace context into every fresh Codex runtime turn, making even a trivial OK response take 25.9 seconds.

How does OpenClaw Codex latency compare to native Codex?

Native Codex App and CLI are significantly faster on the same machine because they don't carry OpenClaw's 30K token context overhead per turn.

Can reducing bootstrap files fix OpenClaw Codex latency?

No — reducing workspace bootstrap budgets did not materially reduce prompt size because the dominant cost is OpenClaw's tool/runtime/channel context, not workspace files.

What model prefix should OpenClaw Codex use?

Documentation disagrees: public docs show codex/gpt-* while installed 2026.5.6 docs recommend openai/gpt-* with agentRuntime.id codex, calling codex/gpt-* a legacy alias.

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clawsmith.com/signal/openclaw-codex-native-runtime-30k-token-overhead-25s-latency

⚠ IssueWide OpenBugLive

OpenClaw Codex Native Runtime Injects 30K Tokens Per Turn — 25.9s Latency for Trivial OK Response

On OpenClaw v2026.5.6, a dedicated Codex agent using native Codex runtime takes 25.9s and sends 33K prompt tokens for a trivial OK response. The dominant cost is OpenClaw's tool/channel/workspace context injection, not workspace bootstrap. Docs disagree on recommended model prefix (codex/gpt-* vs openai/gpt-* + agentRuntime.id). Makes OpenClaw Codex harness unusable for interactive chat vs native Codex App/CLI.

Product Idea from this Signal

A runtime middleware that intercepts OpenClaw agent failures, reasoning leaks, memory timeouts, and processing stalls before they reach end users

446 ▲

OpenClaw agents fail in at least four distinct patterns that existing monitoring tools only detect after the damage is done. Internal reasoning text leaks into user-visible messages across Discord, Telegram, and WhatsApp (9+ open GitHub issues, recurring across versions). Active Memory timeouts kill all conversations after upgrades. Processing lanes stall for minutes with no automatic recovery. Codex runtime injects 30K tokens of overhead per turn making interactive use impossible. This middleware sits between the OpenClaw Gateway and channel outputs, pattern-matches known failure signatures in real time, and either suppresses the bad output (reasoning leaks), force-resets stuck lanes (stalls), or falls back to a cached last-good response (timeouts) before the user ever sees the error.

CLIOPEN-SOURCERELIABILITYMIDDLEWAREDEVTOOL

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