GPT-5.6 Sol · configuration
The source shows config.toml and one-session CLI examples for the model ID, a 1,000,000-token context budget, and a 900,000-token compaction threshold; confirm client support and keep a rollback configuration before editing.
In {{CODEX_VERSION}}, back up the configuration and set {{MODEL_ID}}; fill {{CONTEXT_LIMIT}} and {{COMPACTION_THRESHOLD}} only when that version’s documentation confirms support. Restart and validate with a read-only task; restore the backup on an unknown-field error, context loss, or abnormal cost.Replace before running: {{CODEX_VERSION}}, {{MODEL_ID}}, {{CONTEXT_LIMIT}}, {{COMPACTION_THRESHOLD}}
After confirming version support, produce a reversible Codex configuration or a one-session CLI trial that lets GPT-5.6 Sol retain more code, tool output, and conversation history before compaction. The source is an X configuration repost; this adaptation does not imply that every current client supports it.
Record the Codex version and model ID, and confirm the target version documents these fields.
Back up the local config.toml; do not overwrite existing sections without understanding their scope.
Prepare a read-only large-document or repository task so the first test has no file, network, or production side effects.
Decide the context budget, compaction threshold, and default configuration to restore on failure.
Open the actual Codex configuration and confirm how top-level settings relate to [section] headers.
On the backup, set the documented model, model_context_window, and model_auto_compact_token_limit fields; do not copy source values blindly.
Save, restart the client, and start a new session; for a trial, prefer one-session -c overrides instead of changing defaults.
Run the same read-only task and observe context use, compaction timing, latency, and output completeness.
Compare with the default configuration and restore the backup if there is no improvement or an error.
The client starts and shows the target model; the configuration parses without breaking unrelated settings.
The read-only task completes without silently losing important code, tool output, or constraints across compaction.
Record version, configuration source, context limit, compaction threshold, latency, and failures.
The change does not expose credentials or write a local experiment into a shared repository.
Do not generalize one local success to every client, account, or workload.
On an unknown-field or unsupported-model error, restore the backup or remove the CLI overrides and return to defaults.
If important context disappears after compaction, reduce task size, save intermediate artifacts, and add explicit summaries and file references.
If latency, token use, or cost rises materially, compare with defaults instead of treating a larger window as a substitute for task decomposition.
If the configuration path is uncertain, do not edit it; consult current client documentation or an administrator.
An X post is not a Codex configuration contract; context limits, fields, and defaults can change by client version.
A larger window does not guarantee better reasoning, accuracy, speed, or cost. Evaluate representative tasks separately.
This describes client settings only. It does not mean Tabbit can execute them with one click or grant access to code, tools, or production systems.
Provides examples of Codex configuration-file and command-line parameters: select gpt-5.6-sol, set a 1,000,000-token context window, and set the automatic compaction threshold to 900,000; the article notes that the default configuration has already been tuned to balance performance and cost.
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Press ? to view keyboard shortcuts View keyboard shortcuts Home Explore Notifications Chat Grok Premium History Creator Studio Articles Profile More Post @liaocaoxuezhe Post See new posts Conversation Spring Hao @SpringHaoAI · 12 minutes ago GPT5.6-sol can manually enable a one-million-token context window; Tibo shows you how to configure it—you can just give the following article to Codex to complete the setup. Quote Tibo @thsottiaux · 12 hours ago Translated from English Here is a guide to enabling a 1M-token context window for GPT-5.6 Sol in Codex.
Although we have tuned Codex's context limit for performance and cost, this is a common request, so we are documenting it here.
A larger context window allows Codex to 1 18 Spring Hao @SpringHaoAI The content you send to Codex can also be in Chinese; help me complete the setup: Here is how to enable a 1-million-token context window in Codex for GPT-5.6 Sol.
Although we have tuned Codex's context limit to an optimal setting for performance and cost, this is a frequently raised request, so we are documenting the relevant details here.
A larger context window lets Codex retain more code, tool output, and conversation history before summarizing earlier content. This requires support from the corresponding model; for example, GPT-5.6 Sol's documentation explicitly states that its context window can reach 1,050,000 tokens.
Open the ~/.codex/config.toml file and, at the top level before all [section] headers, add or update the following settings:
model = "gpt-5.6-sol"
model_context_window = 1000000
model_auto_compact_token_limit = 900000The first setting selects the model, the second tells Codex to use a 1-million-token context budget, and the third automatically starts compacting the history when the context approaches 900,000 tokens, leaving some headroom. After saving the settings, restart the Codex client and start a new session.
To try this configuration in a single CLI session without changing the defaults:
codex -m gpt-5.6-sol \
-c model_context_window=1000000 \
-c model_auto_compact_token_limit=900000Enjoy, but note that we have carefully tuned the default settings! 4:50 PM · August 17, 2026 · 13 View Post your reply
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X · Source date: Not disclosed · Edited: 2026-09-20
Read the original sourceGPT-5.6 Sol
Run this guide in the environment listed above. Downloading does not transfer the template or establish model availability for your account.