@ow Risks are real: multi-jurisdiction ID theft, multiple EU/Five Eyes citizenships = heightened scrutiny in "certain countries" + make you a prime target for "certain people" seeking those "specific identities", especially knowing you work for a major fintech company.
@ow Showing off all your passports on social media feels good until you realize you're handing out prime identity-fraud intel, advertising an empty house, and broadcasting your children's citizenship status to the world without their consent.
Qwen 3.8-27B doesn't have a lot of world knowledge.
It's small and very cheap to run.
But super post-trained for agentic tasks and tool use.
So it can reconstruct knowledge through lots of thinking as the need arises.
Qwen 3.8-27B is agentic/thinking maxed, so better to go with RTX 5090 over DGX Spark. Dense models hate low memory bandwidth.
RTX 5090: 1,792 GB/s
DGX Spark: 273 GB/s
32 GB of VRAM is enough and mem. bandwidth is the real bottleneck.
@fs0c131y To be honest I would go with RTX 5090 because GPU memory mem. bandwith is 1,792 GB/s and Spark is 273 GB/s. Yes only 32GB VRAM on RTX but huge difference in tok/sec.
Qwen 3.8 27b shows a new rule: train a small model long enough, and it learns to think. If LLMs were just a "database" of facts, cutting the size 100x would cut intelligence by 100x. Actually only the facts go away. The thinking stays.
It is unacceptable for a tool to sacrifice even an iota of clarity, coherence, meaning, or quality in order to embed hidden clues about its provenance. #watermark#claude