[lumost]

Honestly my anecdotal experience is that fable is benchmaxxed. I have not observed useful gains for Claude since 4.6, with each model iteration making progressively poorer decisions in pursuit of its goal.

The 5.5/5.6 series has performed quite well however. My guess is that my use cases stop aligning to swebench pro around 50% accuracy, and more closely align with DeepSWE.

[maxignol]

> my use cases stop aligning to swebench pro around 50% accuracy, and more closely align with DeepSWE.

What do you mean by that ? If the model is higher than 50% on swebench pro then it tends to drift from what you like it to do, like DeepSWE benchmarks ?

[lumost]

yes, above 50% I don't observe a significant improvement, the models scoring above 65% like opus4.8 seem worse than gpt5.5/opus4.6. DeepSWE appears to align more closely to my personal experience.

[carterschonwald]

this mirrors my approx experience.