Post Contenthttps://www.youtube.com/shorts/TOmMp4SU144
[[{“value”:”Bonsai 2 from PrismML squeezes Qwen3.8 27B into a 6 GB file by retraining every weight to −1, 0 or +1, and PrismML claims it keeps 98% of the full model’s performance. On short tasks it matched the full model in my tests. Then I gave it a real job in an agentic loop: build an ISS tracker on a 3D globe. The full Qwen model built a working tracker. Bonsai never wrote a line of the app. It ran the exact same search 114 times and got the same answer every time.
Compression holds up for chat and quick coding help on a laptop. For long-running agentic tasks, test it on your own tasks before you trust the benchmarks.
Full comparison: [link to the full video]
#Bonsai2 #Qwen #LocalLLM #AIAgents #OpenSourceAI”}]] Read More Prompt Engineering
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