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I built a transformer in C++17 from scratch — no PyTorch, no BLAS, no dependencies. Trains on CPU. 0.83M params, full analytical backprop, 76 min to val loss 1.64.
I built a transformer in C++17 from scratch — no PyTorch, no BLAS, no dependencies. Trains on CPU. 0.83M params, full analytical backprop, 7
Qwen 3.6 wins the benchmarks, but Gemma 4 wins reality. 7 things I learned testing 27B/31B Vision models locally (vLLM / FP8) side by side. Benchmaxing seems real.
Qwen 3.6 wins the benchmarks, but Gemma 4 wins reality. 7 things I learned testing 27B/31B Vision models locally (vLLM / FP8) side by side.
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Anthropic: Claude for Creative Work
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