It wasn't really used enough and it sat in an awkward middle space between luna and sol where either luna high/xhigh or sol med were better cost/perf wise
It probably didn't see that much use, as it struggled to find a niche. If you wanted intelligence tasks, Sol was cheap enough and much smarter. If you wanted performance and cost-effectiveness, Luna was significantly better value while being only a little less intelligent.
Terra ended up just being an awkward middle ground that was not particularly suited for any workload.
I disagree. After a bit of experimenting, I actually found Terra to be a very good workhorse model on none-to-medium reasoning, and I actually quite prefer its code to Sol's in many cases. It has less of a complexity to over-complicate things. Where Sol would have a sea of try/except and recoveries for situations that are structurally impossible, Terra would just write nice, sequential code.
Maybe for one-shotting large things Sol is better, but for prod code where I decompose into smaller tasks and read all the code I favored Terra.
Sol 5.6 was still king for architecture/research in my workflow, though.
Well, naturally people who use it are doing so because they like it. But I'm sure OpenAI is looking at the relative value/usage of Terra next to the other tiers.
Your employer should reconsider. Sol high is cheaper than Terra max and smarter, when measured per task. ie even if tokens are more expensive Sol can often do a job with fewer tokens.
