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This was such a massive upgrade. |
OpenAI saw all the craze going on with Opus 4.7 -- so of course they had to quickly release a new model to steal back the spotlight. |
And these are some pretty incredible upgrades over GPT-5.4 we got here -- no developer should ignore this. |
Like now it's gotten sooo much better at processing extremely long context -- more than 50% increase for very large inputs -- something that will be very useful in development, for those humongous, intricately connected codebases. |
GPT-5.5 doesn’t just extend context to 1 million tokens—it stays sharper inside it, improving Graphwalks BFS accuracy from 92.1% to 94.8% at 0–128K tokens and from 48.3% to 73.7% at 256K tokens. |
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It even comes with a new overpowered thinking mode and a new Pro variant -- to build the most complicated features, and deal with the hardest bugs known to man. |
1. Massive upgrades in long-context reliability |
Many models advertise huge context windows. Few stay accurate when that context becomes truly massive. |
GPT-5.5 ships with a 1 million token context window and a 200,000 token output limit -- but the real story is measurable reliability at extreme scale. |
On Graphwalks BFS, a benchmark that tests whether the model can follow chains of logic scattered across very large documents, GPT-5.5 shows major gains over GPT-5.4 as context size increases: |
At 0–128K tokens, GPT-5.5 scored 94.8%, up from 92.1% for GPT-5.4 (+2.7 points) At 256K tokens, GPT-5.5 scored 73.7%, up from 48.3% (+25.4 points) At the full 1 million token context, GPT-5.5 scored 45.4%, up from 21.4% (+24.0 points)
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