K
pending
Numbeo Mapped 100 Cities on Value — Migration Magnets Lost
Grounded / Real
Inflated / Uruttu
Original Content
You can now run a 2.8 TRILLION parameter model on a 4GB GPU.
It’s called AirLLM, an open-source tool that uses "Layer-wise Inference." It only loads one layer onto your GPU at a time. so the VRAM you need depends on the layer size, not the model size.
No quantization. No distillation. No pruning.
→ DeepSeek-V3 (671B) on 12GB
→ Llama 3.1 405B on 8GB
→ Kimi K3 (2.8 TRILLION params) on under 4GB
→ works with almost every open model
The biggest model on it needs the LEAST VRAM. K3 is sparse MoE, so it streams only the experts a token actually routes to instead of a whole dense layer.
Link: https://lnkd.in/exD-jrwE
2.8 trillion parameters running in less VRAM than a 70B.
It’s called AirLLM, an open-source tool that uses "Layer-wise Inference." It only loads one layer onto your GPU at a time. so the VRAM you need depends on the layer size, not the model size.
No quantization. No distillation. No pruning.
→ DeepSeek-V3 (671B) on 12GB
→ Llama 3.1 405B on 8GB
→ Kimi K3 (2.8 TRILLION params) on under 4GB
→ works with almost every open model
The biggest model on it needs the LEAST VRAM. K3 is sparse MoE, so it streams only the experts a token actually routes to instead of a whole dense layer.
Link: https://lnkd.in/exD-jrwE
2.8 trillion parameters running in less VRAM than a 70B.
Validated Content
Numbeo's Quality of Life Index — which weighs purchasing power, safety, healthcare, housing, traffic, pollution, and climate — shows a consistent pattern: cities like Valencia and Porto combine high quality-of-life scores with comparatively low costs, while high-demand migration hubs like London, New York, LA, and San Francisco score poorly on value once cost is weighed against quality of life. Europe shows the widest cost/quality spread globally, from Switzerland's high-cost/high-quality tier to much cheaper Balkan cities. The claim that Porto, Valencia, and Prague have specifically held the top value spot for seven consecutive years is a historical trend that would need year-by-year archive data to confirm.