Every time they deploy a new model, it feels like older models get slower or dumber. Maybe because of resource allocations, maybe because they started to use quantized models, cant be sure of that.
What i found is that you have to adapt your workflow to the specific model you are using and readapt it every time you notice some problems. Whether of opus4.8, or sonnet5.
The design and layout made it harder to read than it needed to be.
Regardless, the inference costs dropping almost 50× is really amazing to see. And now Kimi K3 release has shown how open models are getting closer to the frontier level already. Open source AI is moving a lot faster than Anthropic and OpenAI would have expected lol.
Its always the feature combinations that get can get to you. Individually i feel like they make sense, but together they can create some surprising vulnerabilities.
This is really neat. They've done some really impressive engineering here ngl with the ~95% KV cache hit rates. MiMo and Deepseek both do seem to get the job done for me. Hope they can keep this pace while staying open source.
You might want to take a look at AionUI. Its a desktop app. I was an early contributor there and they do seem to work on like AI collaborations conversations rather than a single user only chat.
What i found is that you have to adapt your workflow to the specific model you are using and readapt it every time you notice some problems. Whether of opus4.8, or sonnet5.