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49.3
TFLOPS
Syafiq Kamarul Azman
syaffers
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https://syaffers.xyz
syaffers
syafiqkamarulazman
AI & ML interests
Inference and model servers
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🚀 New release: Qwen3.6-27B-A3B-Coder A code-specialized MoE carved out of Qwen3.6-35B-A3B by pure expert pruning — no fine-tuning, no distillation. I profiled all 256 experts on balanced corpora plus targeted code benchmarks (LiveCodeBench + MultiPL-E), built a competence map with the code classes up-weighted 1.5×, and dropped the 72 weakest experts per layer (256→184, ~35B→27B). Router, attention, norms, the MTP head and the vision tower are all preserved; active params stay at A3B and routing is baked to top-10 (revert to top-8 anytime). 📊 Benchmarks (Q6_K, temp 0.6): • MultiPL-E 0.840 • HumanEval 0.970 • LiveCodeBench 0.688 • GSM8K 0.970 · ARC-C 0.944 · AIME 0.733 • GPQA-Diamond 0.773 · MATH-500 0.620 · IFEval 0.730 • Average 0.808 27B footprint, A3B speed, coding that punches well above its size — and the preserved MTP head gives you speculative decoding out of the box (text + vision). 🔗 Model: https://huggingface.co/ManniX-ITA/Qwen3.6-27B-A3B-Coder 📦 GGUF (+MTP): https://huggingface.co/ManniX-ITA/Qwen3.6-27B-A3B-Coder-MTP-GGUF 🦙 Ollama: https://ollama.com/mannix/qwen3.6-27b-a3b-coder
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syaffers/tiny-random-storywriter-base
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about 2 months ago
syaffers/tiny-random-storywriter-base
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syaffers/tiny-random-storywriter-base
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syaffers/Atom-350M-NVFP4
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syaffers/tiny-random-llama-lora
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