... OpenCut AI is the only self-hosted video editor with AI built in. We just added first-class support for MoonshotAI's Kimi K2 a 1T/32B active MoE model that runs entirely locally on TurboQuant. What makes this different: Kimi K2 handles natural language editing commands, script generation, and long-context video analysis all on your hardware Three quantization tiers (Q3/Q4/Q5), so it runs on anything from a laptop to a GPU server Kimi VL A3B adds vision-language understanding ... ... scene analysis and multimodal commands TurboQuant

... OpenCut-AI just shipped real GPU support for TurboQuant KV cache compression. OpenCut-AI is an open-source, local-first AI video editor. Everything runs on your machine transcription, voice cloning, image generation, LLM commands. No cloud, no API keys. The catch was always memory. Running a 7B LLM + Whisper + TTS + Stable Diffusion locally means fighting for every gigabyte of RAM. TurboQuant

... Hunters We just shipped Google Gemma 4 support, paired with our TurboQuant KV-cache compression engine. That means you can now run Google's any-to-any multimodal models directly inside your editor no API keys, no cloud, no data leaving your machine. What's new in this drop: Full Gemma 4 family wired into the hardware-aware model registry: - Gemma 4 E2B (5B) fits in ~3.5 GB, runs on 8 GB laptops - Gemma ... ... sweet-spot for Pro tier - Gemma 4 26B MoE (4B active) big-model quality, efficient inference - Gemma 4 31B Dense top-tier quality for 24 GB+ GPUs TurboQuant

... everyone! We just shipped TurboQuant into OpenCut AI, and this one changes what hardware you need to run the full AI stack. The problem we had OpenCut AI runs everything locally -- LLM, transcription, voice cloning, image generation. That's great for privacy, but brutal on memory. Running the full stack needed 35+ GB RAM. Most of our users have 8-16 GB laptops, so they were stuck with tiny 1B models that gave mediocre scripts, slow commands, and limited context ... ... What TurboQuant