We comprehensively evaluated 16 recent frontier VLMs - including Opus 5.5 and GPT-6 Sol/Luna - on whether higher effort led to better document parsing performance. Higher effort typically leads to improvements on other benchmarks (coding, knowledge work), but up until recently it wasn't obvious that this natively improved capabilities for reading PDFs. Results: ✅ Out of the frontier models, Opus 5.5 has the best performance relative to its price. It's especially good at parsing tables. ✅ Astra is also quite good, but starts at a more expensive price than Opus. ✅ GPT-6 Luna is more compelling at the cheaper end of doc parsing If you're parsing documents at scale, you'll still want a dedicated OCR solution like LlamaParse ( that has better performance at a cheaper price. But if you're parsing docs "in the agent loop" within an app like Codex/Claude code, and you're too lazy to integrate a dedicated solution, then Opus 5.5 is currently the leader. Full results on ParseBench:

.@eightsleep is on track to surpass $1B in lifetime Pod sales by year-end, a defining milestone for our team and the category we set out to build. Pod 6 marks our next phase: making our technology even better and more accessible while expanding into healthcare and medical applications. We believe the future of sleep can have an even bigger impact on health. We’re just getting started. Thank you to Bloomberg for covering the milestone:

Elon's predictions are pretty wild and wishfull at the moment, I'm a big fan but come on he's throwing some really delusional predictions right now, I'm still betting on him and SpaceX but seriously Elon just say we're fucked at the moment and we'll fix it.

Local AI will create so much chaos and don't hate me for this, I'm a big supporter of OSS but let's not pretend that it's okay that a teenager in his basement can download an open model on his gaming machine and hack into the whole neighborhood and NO i don't know how we can handle this dilemma.