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
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.
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.
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
I don't agree. In "none" thinking mode, Terra serves a useful purpose where medium-grade intelligence is needed. Luna doesn't cut it.
Hardly enough time had passed to develop the data to come to a conclusion. Users can take time to build interest.
I'm scared now, my employer only allows Luna and Terra on 5.6. I really hope they will allow Sol then on GPT 6.
Funny thing is they very recently also set a real limit per-user/month, so why even limit the models because theyre "too expensive".
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.
I read that there are rumors that they're getting rid of that tier. No idea where the rumor came from, though. This lends credence to it, I suppose.
Sol price is halved so no need for terra
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.
I have found it worked quite well as the workhorse model in my hermes agent.
The users of Terra disagree. Specifically, Terra is useful when medium-grade intelligence is needed in instant ("none" thinking) mode.
Hardly enough time had passed to develop the data to come to a conclusion. Users can take time to develop an interest.