
Our mission is to advance AI to benefit everyone. @GagaAI_official & @magiai_hq are out now.
Joined March 2025
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🪄 MAGI-2 Preview: The Open-Source 100B+ Ultra-Fine-Grained MoE Video Generation Model
📄 Tech Report: sand.ai/blog/magi-2-preview
💻 GitHub: github.com/SandAI-org/MAGI-2…
🏆 114B total parameters, with only 6B activated per token for top-tier performance
🔓 100% open-source & tech report
💰 1/10 the generation cost of mainstream models
⏳ 1/7
Open AI for everyone. Proudly supporting the open-source community. Explore and try it yourself 👇
💻 GitHub: github.com/SandAI-org/MAGI-2…
🤗 Hugging Face: huggingface.co/sand-ai/MAGI-…
⏳ 6/7
Thanks for making it all the way here. 🙌
New coordinates set. Sand.ai is now live.
The frontier is everywhere. Drop by often—more signals are on the way. 🪄
⏳ 7/7
🪄 Introducing MagiCompiler: Break the Boundaries of Local Compilation for Large Models.
MagiCompiler is a unified compilation framework advancing torch.compile into a global "Compiler as Manager", conquering the VRAM and compute walls for training & multi-modality inference.
- Repo: github.com/SandAI-org/MagiCo…
🌟 Highlights:
- Whole-Graph & FSDP-Aware Compilation: Breaks local boundaries. Full-graph capture for inference & layer-wise compilation for FSDP training to maximize aggressive cross-op fusion.
- Heuristic Recompute: No more manual checkpointing. Auto-preserves compute-bound ops (e.g., Attention) and recomputes memory-bound ones to slash peak VRAM seamlessly.
- JIT Extreme Offloading: Smart Compute + H2D dual-stream overlap. Keeps high "cost-performance" weights in VRAM and prefetches the rest at the last millisecond to eliminate pipeline bubbles.
- Plug-and-Play: Just 2 decorators (@magi_compile & @magi_register_custom_op) deliver system-level optimizations without complex model refactoring.
🪄 Introducing MagiAttention v1.1.0: Defining the Performance Ceiling for Hopper & Blackwell Architectures.
MagiAttention is a distributed attention engine sharing the bottlenecks of ultra-long context and heterogeneous masks.
- Repo: github.com/SandAI-org/MagiAt…
- Blog: sandai-org.github.io/MagiAtt…
🌟 Highlights:
- Blackwell Support: Early Blackwell support via FFA_FA4 backend, leveraging HSTU function & R2P optimizations for next-gen hardware.
- Native Group Collective: DeepEP-inspired fused kernels (GroupCast/GroupReduce) to break RDMA bottlenecks and achieve zero-redundancy communication.
- Mask-Agnostic SOTA: Constant high-throughput performance even for irregular, complex masks. No more OOM or performance drops in "hard mode."
- System-Level Synergy: Dispatch Solver + Adaptive Overlap ensures near-linear scalability on H100 & B200 clusters.
📊 Performance & Benchmarks: Beating Open-Source SOTA
Great architecture is nothing without results. We benchmarked daVinci-MagiHuman against leading models like LTX-2.3, Ovi 1.1, and MoVA. The results speak for themselves:
👥 Human Blind Evals: Tested on a 100-sample dataset across multiple dimensions, achieving a massive 70.5% overall win rate!
📈 Objective Metrics:
🎬 Video (VideoScore2): Outperforms LTX-2.3 in Visual Quality & Text Alignment; superior to Ovi 1.1 across the board.
🎙️ Audio (TalkVid-Bench): Crushes the competition with vastly lower Word Error Rates (WER) for crystal-clear, accurate speech.
⏳ 5/6
Thanks for reading! 🙌
Come visit us at Sand.ai to see what else we're building. We are incredibly proud to contribute to the open-source community and will keep pushing the boundaries of AI!
⏳ 6/6
Sand.ai retweeted
The full version of Gaga-1 is here.
🎙️ Voice Reference
📱 Both 16:9 & 9:16 Video
✨ 1080p Export
Free for all. Create now.
The full version of Gaga-1 is here.
Sand.ai retweeted
GAGA-1 is out now. Free for all. No invite needed.
GAGA-1 is out now!
GAGA-1: The Holistic AI Actor. Voice, Lipsync, and Performance as One.





