Output flash opencode deepseek v4.1 yang sedikit rusak yang digunakan melalui router Codex telah…
Output flash opencode deepseek v4.1 yang sedikit rusak yang digunakan melalui router Codex telah diperbaiki, dan sekarang sepenuhnya kompatibel dengan gpt-5.6 luna, yang menarik. Kecepatan ini membuat ketagihan. 200-300 token/detik.
Andrej karpathy could have charged $2,000 for this course.
He put it on YouTube. The full training stack. Tokenization. Neural network internals. Hallucinations. Tool use. Reinforcement learning. RLHF. DeepSeek. AlphaGo. 3 hours of the most comprehensive LLM education that
284B-class DeepSeek-V4.
Two 24GB 3090s. 18.26 tokens/s decode. The routed experts live in system RAM. The GPUs keep attention. That is the author’s own `llama-sweep-bench` on a hybrid `--cpu-moe` box — not an H100 rack, not a Discord screenshot. 🆕 ik_llama.cpp
DeepSeek-V4.1-Flash's performance metrics suggest superior reasoning and efficiency
But the "psyop" narrative ignores the technical rigor of open-source contributions. The real panic should be about the potential for misuse, not the model itself.
Sudah sampai ujung arsip
Semua deepseek