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What is the context window?

Every session window has a context-length limit. Above the chat box you can see how much context the current window has used — for example the 30.2k / 300.0k below: the left number is the used session size, and the right number is the current session’s context ceiling. The context progress bar above the chat box, showing 30.2k used and a 300.0k ceiling

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Setting the context ceiling

A single session’s context ceiling is determined by the model’s capability; today’s mainstream models already support up to 1M. SoloEnt lets you set the per-session context ceiling to a reasonable level as needed. The Context window dropdown in model settings, letting you choose between the 300K and 1M tiers
Bigger is not always better. An oversized window scatters the model’s attention — especially during repeated exploration and revision, performance can actually drop.
  • Keep it around 200K–300K.
  • Common practice: following mature Agent products like Codex Cloud, people usually use only the first tier (200K–300K) of context and rarely go higher.

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Why we don’t recommend maxing out a single 1M window

Many users assume a single window brings caching advantages, but some models charge in tiers based on session size, so an overly long session risks a cost surge.
Example: with some models, input/output below 256K is one price tier, and above 256K it rises noticeably — a clear tiered price jump.
While most new models offer good caching (a cache hit may cost only 1/5 to 1/10 of the price), sessions spanning days or long idle gaps cause the cache to expire, so a single request consumes a lot of tokens.
If you switch models partway through a single window, the new model actually has to read all the context the old model accumulated, which can consume a large chunk of the session at once — very uneconomical. Always summarize the prior session before switching models.

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Best practices

Switching windows means giving up the current window’s session history, which feels wasteful to many users; but over-relying on a single window is neither economical nor good for long-term context quality in practice.
  • Task isolation: aim for “one session, one task,” and check completion before moving on.
    • If the next task is related: summarize the current session, offload it to a project file (such as SOLOENT.md), then continue in a new session.
    • If the next task is unrelated: decisively open a new session to avoid piling up historical tokens.
  • Use session compaction: when a session gets too full, use the /compact command to condense the current content into a short summary and use it as the starting input for a new session — preserving the core information while lowering token usage.
The default-command hint shown when typing /compact in the chat box: compact the current session to free up context space
  • Once context usage passes about 200K, continuing may cause a cost surge; a good rule of thumb is to consider opening a new window when a single window reaches 100–150K.

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Always summarize and offload before opening a new window

  1. Long-form fiction: use /init to generate SOLOENT.md in your project and write key context — characters, outline, current progress — into it. Each new window lets the model quickly restore the full project picture by reading SOLOENT.md, rather than relying on context accumulated in a single session.
  2. After heavy discussion: if you and the Agent have discussed a lot and context is running high, ask the Agent to summarize the current discussion before switching windows (or models) and land the conclusions in a readable document. After switching, read that document first to get back up to speed.

SOLOENT.md Guide

Use a memory file to carry long-term context so every new session quickly restores the full picture

Commands

Learn how to use built-in commands like /compact and /init