Taipei City, Taiwan
Joined April 2013
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My iPhone Duo video went viral, so I'm giving away 100 iPhones on X 😛
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ฅʕ •ﻌ•ʔฅ retweeted
用一句话夺走你的卧槽。 claude-opus-5-5.riba2534.cn
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ฅʕ •ﻌ•ʔฅ retweeted
made a little game for myself and the gameplay is too good to keep, so now it’s the new 404 for @iskra_graphics you can play it right now at iskra.graphics/404
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jo-nike.github.io/h3-turbo-e… this repo compares a lot of them
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ฅʕ •ﻌ•ʔฅ retweeted
The worst part of doing dev work on a Mac: .DS_STORE
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🤔 llama-server (4f13cb7) M3 Max 128G -m unsloth/Qwen3.6-27B-MTP-GGUF/Qwen3.6-27B-UD-Q4_K_XL.gguf \ -ngl all -c 8192 -ub 2048 -np 1 -fa on -ctk q8_0 -ctv q8_0 \ --temp 0.6 --top-p 0.95 --top-k 20 --min-p 0 \ --reasoning off \
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ฅʕ •ﻌ•ʔฅ retweeted
Six open-source LLMs. One sliding puzzle. A brutal test of long-horizon reasoning and tool calling. Five of them broke. One didn't. I gave each model a move_tile tool and a scrambled 3×3 board, then asked it to solve the puzzle through pure turn-by-turn reasoning. The deeper the scramble, the more brutal the search. Five runs per depth, best run kept. A model fails the round if it exceeds 6x the optimal move count. > Depth 5: Everyone solves it. Yawn. > Depth 10: GLM 5.1 melts down. 43 moves. Cut. > Depth 12: Gemma4 26B loses the plot, shuffling tiles in circles. Gone. > Depth 15: The wall. DeepSeek V4 Flash, out. DeepSeek V4 Pro, out. Gemma4, out again. GLM 5.1, out. Two survivors: Qwen3.6 35B-A3B, and Kimi K2.6 with an 11-move solve that looked like cheating. > Depth 18: Same two. Everyone else hallucinating tiles that weren't there. > Depth 22: Final boss. Kimi, flawless for five rounds, finally cracks. 81 moves. Still scrambled. DeepSeek V4 Pro limps home at 90. Qwen3.6 35B-A3B solves it in 36. The smallest model in the room. ~3B active params. Fits on a single 3090. It beat everything. Kimi was elegant. Qwen3.6 was unstoppable.
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ฅʕ •ﻌ•ʔฅ retweeted
🚀 Meet Qwen3.6-27B, our latest dense, open-source model, packing flagship-level coding power! Yes, 27B, and Qwen3.6-27B punches way above its weight. 👇 What's new: 🧠 Outstanding agentic coding — surpasses Qwen3.5-397B-A17B across all major coding benchmarks 💡 Strong reasoning across text & multimodal tasks 🔄 Supports thinking & non-thinking modes ✅ Apache 2.0 — fully open, fully yours Smaller model. Bigger results. Community's favorite. ❤️ We can't wait to see what you build with Qwen3.6-27B! 👀 🔗👇 Blog: qwen.ai/blog?id=qwen3.6-27b Qwen Studio: chat.qwen.ai/?models=qwen3.6… Github: github.com/QwenLM/Qwen3.6 Hugging Face: huggingface.co/Qwen/Qwen3.6-… huggingface.co/Qwen/Qwen3.6-… ModelScope: modelscope.cn/models/Qwen/Qw… modelscope.cn/models/Qwen/Qw…
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Quantization can make an LLM 4x smaller and 2x faster, with barely any quality loss. But what *is* it? @samwhoo crafted a beautiful interactive essay explaining it from first principles, aimed at coders, not mathematicians. ngrok.com/blog/quantization
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サンド詐欺
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ฅʕ •ﻌ•ʔฅ retweeted
Would you like to be doodled? High-res portrait giveaway! RT & follow to enter. Winner announced 18/05 9PM GMT <3
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