GPT-5.5 shows limited impact from context compression, developers find

OpenAI’s GPT-5.5 appears remarkably unfazed by having its context squeezed. Developer experimentation since the model’s April 2026 launch has revealed that compressing the information fed into GPT-5.5 doesn’t meaningfully degrade its output quality, though it does push the model to lean harder on its retrieval capabilities to fill in the gaps. A million tokens and something to do with them GPT-5.5 launched on April 23, 2026, with a 1 million token context window available through the API. To put that in perspective, a million tokens is roughly 750,000 words, or about ten full-length novels worth of text that the model can process in a single pass. The raw retrieval numbers back up the ambition. On OpenAI’s MRCR v2 8-needle evaluation, a benchmark that tests a model’s ability to find specific information buried deep in enormous contexts, GPT-5.5 scored 74.0% at the 512K to 1M token range. Its predecessor managed just 36.6% on the same test. Processing all that context is expensive, both in compute costs and response latency. Which is why developer tools like Hermes Agent and the Codex integrations have turned to context compression as a practical workaround. Compression without cata...