Allow opt-in full 1.05M context and configurable compaction for GPT-5.6 Sol

What variant of Codex are you using?

Codex App and Codex CLI with GPT-5.6 Sol on a ChatGPT Pro subscription.

What feature would you like to see?

Allow advanced users to opt into the full context window supported by GPT-5.6 Sol and configure when automatic compaction occurs.

The current default can remain optimized for cost, latency, and general use. The requested change is an explicit advanced option, not a change to the default behavior.

A suitable implementation could:

• Allow model_context_window to be configured up to the maximum supported by the selected model, including the full 1.05M window for GPT-5.6 Sol.
• Allow model_auto_compact_token_limit to be configured independently within that effective window.
• Expose equivalent controls in the Codex App for users who do not edit config.toml.
• Clearly display the effective context window and automatic-compaction threshold for the active session.
• Apply a higher usage multiplier, consume additional credits, or permit paid overage when a larger context tier is selected.
• Keep the existing smaller window and current compaction behavior as the default.

This is important because compaction is useful but lossy. During long debugging sessions, architecture analysis, repository-wide refactors, and research-heavy implementations, summaries can omit small decisions, failed approaches, constraints, and relationships between files that remain relevant later.

I recently completed a long, tool-heavy coding task using GPT-5.6 Sol through GitHub Copilot. After many iterations, the session reported roughly 260K tokens used out of the 1.05M context window without requiring compaction. In daily Codex use, comparable workflows commonly trigger one or more compactions much earlier. This creates a material continuity difference even when the underlying model is the same.

I am not requesting free, unlimited 1M context. As a ChatGPT Pro user, I would willingly accept higher quota consumption or additional charges for selected sessions where preserving raw context is more valuable than minimizing usage. The core request is user control over the cost, latency, and context-retention tradeoff.

Additional information

Related issues:

• #19464 requested opt-in 1M context for GPT-5.5. That issue remains open but its conversation is locked, so updated GPT-5.6 Sol feedback cannot be added there.
• #31860 documents the gap between the GPT-5.6 Sol API context specification and the smaller effective Codex window.
• #32806 documents a subsequent reduction in the effective GPT-5.6 Sol context exposed by Codex.

This issue is intentionally filed as a feature request rather than a bug report. It asks for a supported opt-in mechanism, transparent effective limits, and an explicit usage multiplier rather than assuming the full model context must be included in the default subscription behavior.