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| title: VKIE — VIDRAFT Kernel Inference Engine | |
| emoji: 🚄 | |
| colorFrom: purple | |
| colorTo: indigo | |
| sdk: static | |
| pinned: true | |
| license: apache-2.0 | |
| short_description: VKIE (비키) — VKAE accelerates, VKUE saves, VKIE maximizes | |
| # 🚄 VKIE (비키) — VIDRAFT Kernel Inference Engine | |
| The unified control tower for VIDRAFT's inference line, across three axes: | |
| - 🏎️ **VKAE** — GPU **acceleration** (the sports car): ~9× faster single-stream on a B200. | |
| - 🚗 **VKUE** — GPU **savings** (the compact car): 34.7B on a FREE CPU, no GPU. | |
| - 🚄 **VKIE** — accel + savings = **max serving** (the train): 18,057 tok/s on one B200. | |
| Every number is measured; every demo is live (they run on their real hardware, embedded or linked here). The "after" figures come from VIDRAFT's optimized serving — results are public, engine internals are proprietary. | |
| Links: VKAE · VKUE · GPU-vs-CPU · CPU-only · FREE CPU · Image (T4) · Model · Blog. | |