🚨MOSS-VL-Realtime now runs through a complete browser-to-GPU stack @Open_MOSS 💡Realtime Demo: a browser app for live voice/video interaction — video calls, screen sharing, and interruption, no installation needed 🛠️ SGLang-Omni: a specialized inference backend that keeps real-time video calls smooth under concurrent users 🧠 Long-term memory: sliding-window video memory + on-demand recall, so the assistant remembers what you talked about even in long conversations → Bring up the full pipeline with a one-click installer The full model-to-application pipeline is now open source. The third_party directory also includes a FlashAttention-3 module customized for MOSS-VL; mainline @sgl_project support for offline batch inference is already merged into upstream SGLang. 🔥Stay tuned for our real-time API and online Playground without needing to prepare your own GPU! More details below ↓

MOSS-VL is now supported in the ms-swift main branch 🚀 Multimodal data—including images and videos—can now be used directly in the existing supervised fine-tuning (SFT) workflow. Two fine-tuning options have been validated: • LoRA: A lower-cost way to validate new datasets and tasks • Full SFT: Jointly trains the language model, vision module, and alignment module 🔄 Fine-tuned checkpoints can also be loaded directly with Swift for inference. In our basketball-game test, fine-tuning improved all three evaluated metrics: 🏀 JSON/schema validity rate: 98.18% → 100% 🏀 Event-type LCS precision: 82.35% → 100% 🏀 Jersey-color accuracy: 34.12% → 57.65% Special thanks to @ModelScope2022 for the support 🙌 Try MOSS-VL with ms-swift 👇

MOSS-VL is now supported in LlamaFactory @llamafactory_ai MOSS-VL has been merged into the LlamaFactory main branch, making it easy to fine-tune for your own domain. You can now fine-tune MOSS-VL for image, video, and other multimodal tasks using the familiar LlamaFactory workflow — from data preparation and training to checkpoint resume and inference. What’s been validated end-to-end: 🚀 LoRA fine-tuning — ideal for fast, low-cost experimentation ⚡ Full fine-tuning — for deeper domain adaptation 🖥️ WebUI — configure models, datasets, and training parameters without writing a custom training script 🔄 Complete training workflow — training, saving, checkpoint resume, inference, and weight merging are all supported Resources 👇

24GB VRAM is enough to run MOSS-VL locally.@Open_MOSS We’ve released FP8 and NF4 versions for both MOSS-VL-Instruct and MOSS-VL-Realtime — covering image, video, and real-time streaming understanding. 🖼️ MOSS-VL-Instruct — image & video understanding Built for local inference, batch processing, and serving. 🎥 MOSS-VL-Realtime — understand video as it happens Built for cameras, livestreams, and continuous video analysis, with timestamp-aware streaming understanding that continuously responds as the video unfolds. Each model now comes in two quantization options: ⚡ FP8 — balances model capability and inference performance ⚡ NF4 — pushes VRAM usage even lower and can run stably within 24GB VRAM For real-time video understanding, we recommend MOSS-VL-Realtime-NF4 for more VRAM headroom and a more stable long-context experience. FP8 is a good fit when context length is more controlled. We also compared all four quantized checkpoints with their original BF16 models across selected image, video, and real-time streaming benchmarks. Overall, performance remains close to BF16 while VRAM usage drops substantially — making MOSS-VL much easier to deploy on 24GB consumer GPUs. All 4 checkpoints are available now ↓ 🖼️ MOSS-VL-Instruct-0708-FP8 🤗 Hugging Face: huggingface.co/OpenMOSS-Team… 🌐 ModelScope: modelscope.cn/models/openmos… 🖼️ MOSS-VL-Instruct-0708-NF4 🤗 Hugging Face: huggingface.co/OpenMOSS-Team… 🌐 ModelScope: modelscope.cn/models/openmos… 🎥 MOSS-VL-Realtime-FP8 🤗 Hugging Face: huggingface.co/OpenMOSS-Team… 🌐 ModelScope: modelscope.cn/models/openmos… 🎥 MOSS-VL-Realtime-NF4 🤗 Hugging Face: huggingface.co/OpenMOSS-Team… 🌐 ModelScope: modelscope.cn/models/openmos…

We're at WAIC 2026! @MosiAI_Official & @Open_MOSS is bringing MOSS Context Intelligence Park to Shanghai! 📍世博展览馆 Booth H1-C1234｜📅 July 17–20 Experience how AI listens, sees, understands context, and creates in the real world: 🔊 Voice Babel Tower - light up a 5m AI voice installation with your own voice 🎙️ Mossland Creator Booth - immersive AIGC creation with AI voice ❓ VBTI - discover your voice personality 🤖 Live demos of MOSS-TTS, MOSS-Transcribe-Diarize & MOSS-VL-Realtime Come meet us at WAIC 2026! 🌏 #waic2026