…The biggest con for me was the cost and token usage. Because it reads so much context to be accurate, you can burn through your limits quickly if you aren’t careful…
…model's parameters per token, and deliver a quality of output that was previously only accessible through larger, denser models at a fraction of the memory cost. The result is that my…
…and others increasing subscription costs over time, as PC hardware becomes more expensive and these companies need to show revenue growth for their IPOs. The biggest argument in favor of local AI…
I use Claude Pro, Qwen 3-Coder, and Gemma 4 together, and it's the most cost-efficient AI workflow I've ever built
…1.35x more tokens than Opus 4.6. In other words, the exact same prompt you were running before could now cost you up to 35% more. And that's before you…
…VRAM has ceased to be the be-all and end-all of local AI hardware, with the focus shifting to a more balanced approach, combining memory capacity and bandwidth in flexible configurations…
…Fable 5 was already difficult to justify economically The shutdown came before the subscription cutoff Fable 5 cost $10 per million input tokens and $50 per million output tokens, double Opus 4…
…the extended token usage disabled. The productivity angle here is pretty straightforward. Most AI tools start losing the thread as a conversation gets longer, or force you to summarize and re-paste…
…Claude 3 models support up to 200,000 tokens in their context window. This is one of the largest context windows of any mainstream AI assistant, and Claude Projects is built to…
…It's worth noting that for routine back-and-forth tasks, I saw almost no productivity gain over Opus 4.8. Fable 5 was expensive and burned through many tokens. For the…
