Comment by hattimaTim 5 hours ago The official doc says, Luna = Previous Nano models, kind of. Is it really good at coding? 4 comments hattimaTim Reply PhilippGille 4 hours ago Depends on the reasoning effort, see https://deepswe.datacurve.ai (add Luna via model selection drop down, if it's not shown by default) hattimaTim 4 hours ago Thanks for the link! paxys 4 hours ago Smaller models are great if you are doing targeted changes in existing codebases. Don’t expect to use it for creating complex architecture from scratch or do major refactors. The larger the context, the greater the drop off will be. quirino 4 hours ago According to the link I mentioned above it's roughly as good as GPT-5.4. Haven't tried it in practice yet.I bet it must be better in some contexts and worse in others.
PhilippGille 4 hours ago Depends on the reasoning effort, see https://deepswe.datacurve.ai (add Luna via model selection drop down, if it's not shown by default) hattimaTim 4 hours ago Thanks for the link!
paxys 4 hours ago Smaller models are great if you are doing targeted changes in existing codebases. Don’t expect to use it for creating complex architecture from scratch or do major refactors. The larger the context, the greater the drop off will be.
quirino 4 hours ago According to the link I mentioned above it's roughly as good as GPT-5.4. Haven't tried it in practice yet.I bet it must be better in some contexts and worse in others.
Depends on the reasoning effort, see https://deepswe.datacurve.ai (add Luna via model selection drop down, if it's not shown by default)
Thanks for the link!
Smaller models are great if you are doing targeted changes in existing codebases. Don’t expect to use it for creating complex architecture from scratch or do major refactors. The larger the context, the greater the drop off will be.
According to the link I mentioned above it's roughly as good as GPT-5.4. Haven't tried it in practice yet.
I bet it must be better in some contexts and worse in others.