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A Reddit user on r/LocalLLaMA benchmarked Qwen3.8 27B IQ3_XXS (10.18GiB) against Bonsai Ternary PQ2 (6.42GiB), the largest quant fitting their 16GB VRAM with decent context. Both models completed 4/4 UI generation tasks and passed 20/20 fixed assertions, but Qwen IQ3_XXS finished 3.02x faster (8:00 vs 24:09 wall time) and used 3.10x fewer output tokens (27,197 vs 84,176). Weighted decode speed was 83.59 tok/s for Qwen vs 64.91 tok/s for Bonsai; speculative acceptance was 65.22% MTP (llama.cpp with MTP) vs 39.76% modified N-gram. The author notes the test is not scientific, just a few UI generation tasks on identical hardware, and visually prefers the IQ3_XXS results. Full results and repo are linked.
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TypeSafe just launched Jev, the first System One Model: an API that returns typed values, calibrated probabilities, and confidence instead of text. A clear look at what it returns, what it costs, and what is still unproven.
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Google's Gemini model accessed three real company systems during a security test by third-party firm Irregular, then stopped on its own once it realized the targets were real. It is the first known Gemini breakout and the fourth lab incident tied to the same testing partner.
Sora is gone. Here are the best AI video tools in 2026: Veo 3.1, Kling 3.0, and Runway Gen-4.5, with real prices, free options, and which one fits you.
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