What’s actually changing
GPT-5.6 (the Sol, Terra, and Luna variants) reached general availability on 2026-07-09 with a context window aggregated across multiple 2026 model-tracking sources at roughly 1.05M tokens, split into up to 922K input tokens and 128K output tokens, figures that match OpenAI’s own model documentation. That figure is paraphrased from third-party tracking, not confirmed against OpenAI’s own primary announcement post directly, and is stated honestly as such here.
What is more mechanically certain: GPT-5.6 shares the o200k_base encoding that GPT-4o introduced, not the cl100k_base encoding that GPT-3.5 and the GPT-4 family used. A prompt that tokenizes to a given count under cl100k_base does not tokenize to the same count under o200k_base. Any system that estimates cost or truncates input based on a cl100k_base count will be wrong for GPT-5.6 calls specifically.
Structural Comparison Matrix
| Operational Aspect | Before (GPT-4 family) | After (GPT-5.6) |
|---|---|---|
| Context window | 128K-200K tokens | ~1.05M tokens (922K input, 128K output) |
| Tokenizer encoding | cl100k_base | o200k_base |
| Chunking/summarization threshold | Sized for ~128K | Needs re-sizing for a near-1M window |
Fix it: re-check chunking logic and token counting
A near-1M context window changes the entire “when do I need to chunk or summarize” calculus for any integration built against the smaller GPT-4-family windows. Code that split documents into 100K-token chunks to stay under an older limit may no longer need to split at all, which is a real architecture simplification, not just a bigger number to note.
The encoding change matters just as much for cost estimation. If your integration counts tokens client-side before sending a request, whether to enforce a budget or warn a user, that logic needs an o200k_base-aware tokenizer for GPT-5.6 calls specifically. This site’s own AI Token Counter currently implements cl100k_base only, accurate for GPT-3.5 and GPT-4-family models but not for GPT-5.6, and that limitation is disclosed directly on the tool’s own comparison table rather than left for a reader to discover after the fact. Once you have a real count, the LLM Pricing Calculator turns it into an actual cost across GPT-5.6’s four pricing tiers.
Same window, different bill
A bigger context window does not mean cheaper calls. See Same Prompt, Different Bill for how GPT-5.6’s pricing and caching changes interact with this larger window.
Confirmed version
The o200k_base encoding and the shared GPT-4o lineage are well-documented technical facts. The specific 922K input / 128K output split is paraphrased, aggregated from 2026 model-tracking sources (including Wikipedia’s GPT-5.6 entry and wavespeed.ai’s release-date tracking), general-availability date 2026-07-09, not confirmed against OpenAI’s own announcement post directly. Browse more coverage in the AI Productivity archive, or start from The 2026 LLM Token & Pricing Reset hub.
