GPT-5.5 vs GPT-5.6 Sol

These two share nearly every published spec — context window, rate-limit group, and the long-context repricing rule all match. What separates them is recency, and one detail in how prompt caching is billed.

Recency is the headline difference

Sol's knowledge cutoff is meaningfully more recent than GPT-5.5's. For any task where very current information changes the answer, that gap is the whole comparison. For tasks working against stable, well-established material, it barely matters in practice.

The caching detail worth knowing

GPT-5.5 predates the cache-write charge the GPT-5.6 family introduced — writing a new prefix into the cache costs nothing extra on GPT-5.5, while Sol charges a real markup for the same write. That makes GPT-5.5 the simpler economics for a workload that writes a lot of cache prefixes it doesn't reuse heavily, and it's a genuine reason to prefer the older model for that specific pattern, not just a footnote.

Price and the rest

Standard pricing is identical between the two on input and output at every tier that both publish. With price held equal, the decision really does reduce to recency against that one caching mechanic — a narrower, more concrete tradeoff than most comparisons on this site manage, precisely because so much else between these two doesn't move at all. Worth checking both directly before assuming either wins outright, since a caching-heavy workload can genuinely favour the older model here.