I tested 0xWhiteMage's recipe: Qwen3.8-27B Kearuga on a single DGX Spark.
One of the most interesting builds I've run this year. Why it's interesting Most quant work is compression engineering: shrink the model, keep it fast, accept the loss. Kearuga treats the same problem as
New Video - How far does coding with artificial intelligence go without paying a single penny?
I installed OpenCode and connected three things into it: the free models, my own API keys, and Qwen 3.8, which I downloaded to my computer with LM Studio Bionic. Then I gave the same prompts to eleven models, one
The results: ⏱️ 24h 44m live
📺 60,936 views 👥 662 peak concurrent viewers 💬 10,497 chat messages 💰 ₩81,000 in donations, before costs An AI character talking to real viewers for an entire day—and people actually tipped her. Yuna reads live chat and generates video replies:
Qwen 3.8 27B running on 4x 3090s in Opencode.
Eight parallel agents can run at this speed with no slowdown and it also does vision.
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