FlagOS is a fully open-source system software stack for heterogeneous AI chips. It unifies the model–system–chip layers to enable a "develop once, run anywhere" workflow, eliminating the fragmentation among vendor-specific software stacks and substantially lowering the cost of porting AI workloads across accelerators. In this release, Qwen-Image-2.1 leverages the FlagOS software stack to provide direct multi-chip support. By integrating the Triton-based operator library FlagGems via the Torch-FL plugin, FlagOS enables seamless adaptation of the Diffusers library across chip platforms; the usage experience remains identical to that on NVIDIA, requiring zero code modifications. Inference…
Organization
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Models in Library7
Datasets in Library0
Models on Hugging Face312
Followers40
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Models
Hy3 is Tencent Hunyuan team's next-generation MoE large model with integrated fast and slow thinking: 295B total parameters, 21B active parameters (plus 3.8B MTP layer parameters), 192 experts with top-8 activation, supporting 256K context. Compared to the Preview version released in late April, Hy3 has achieved a comprehensive leap in intelligence through incorporating real-world business feedback, scaling up RL compute, and improving post-training data quality, significantly outperforming open-source models of similar size. - Out-of-the-box inference scripts with pre-configured hardware and software parameters - Released FlagOS-Nvidia container image supporting deployment within minutes…
Alibaba open‑sources the vision‑language model Qwen3.8‑27B, and the Zhongzhi (众智) FlagOS community simultaneously completes Day 0 multi‑chip adaptation; based on the FlagOS unified open‑source technology stack, Qwen3.8‑27B has finished multi‑chip adaptation, precision alignment and deployment verification across 11 AI chips including T-Head（平头哥）、NVIDIA（英伟达）、Moore Threads（摩尔线程）、MetaX（沐曦）、Kunlunxin（昆仑芯）、Ascend（华为昇腾）、Hygon（海光）、Iluvatar CoreX（天数智芯）、Tsingmicro（清微智能）、Enflame（燧原科技）and Sunrise（曦望）, among which NVIDIA and Moore Threads support FP8 precision deployment while the rest run on BF16, and FlagOS has for the first time extended the adaptation of the latest Qwen model to ARM edge‑side…
Alibaba open‑sources the vision‑language model Qwen3.8‑27B, and the Zhongzhi (众智) FlagOS community simultaneously completes Day 0 multi‑chip adaptation; based on the FlagOS unified open‑source technology stack, Qwen3.8‑27B has finished multi‑chip adaptation, precision alignment and deployment verification across 11 AI chips including T-Head（平头哥）、NVIDIA（英伟达）、Moore Threads（摩尔线程）、MetaX（沐曦）、Kunlunxin（昆仑芯）、Ascend（华为昇腾）、Hygon（海光）、Iluvatar CoreX（天数智芯）、Tsingmicro（清微智能）、Enflame（燧原科技）and Sunrise（曦望）, among which NVIDIA and Moore Threads support FP8 precision deployment while the rest run on BF16, and FlagOS has for the first time extended the adaptation of the latest Qwen model to ARM edge‑side…
Alibaba open‑sources the vision‑language model Qwen3.8‑27B, and the Zhongzhi (众智) FlagOS community simultaneously completes Day 0 multi‑chip adaptation; based on the FlagOS unified open‑source technology stack, Qwen3.8‑27B has finished multi‑chip adaptation, precision alignment and deployment verification across 11 AI chips including T-Head（平头哥）、NVIDIA（英伟达）、Moore Threads（摩尔线程）、MetaX（沐曦）、Kunlunxin（昆仑芯）、Ascend（华为昇腾）、Hygon（海光）、Iluvatar CoreX（天数智芯）、Tsingmicro（清微智能）、Enflame（燧原科技）and Sunrise（曦望）, among which NVIDIA and Moore Threads support FP8 precision deployment while the rest run on BF16, and FlagOS has for the first time extended the adaptation of the latest Qwen model to ARM edge‑side…
ModelBest, together with OpenBMB, has open-sourced the next-generation on-device multimodal large model MiniCPM-V4.7, releasing two variants at once: 1B and 35B-A3B (MoE). The Zhongzhi FlagOS community completed day-0 cross-chip adaptation covering 12 platforms — T-Head, NVIDIA, Huawei Ascend, Hygon, Kunlunxin, MetaX, Moore Threads, Tsingmicro, Iluvatar CoreX, Sunrise, Mac (M5 Pro), and CIX P1 — based on the FlagOS unified multi-chip software stack. Model images are now live on ModelScope and HuggingFace simultaneously. This adaptation extends both variants to ARM edge CPU platforms as well, enabling a viable deployment path for multimodal understanding on both data-center and end-user…
ModelBest, together with OpenBMB, has open-sourced MiniCPM-V4.7, a next-generation on-device multimodal large model, releasing two variants at once: 1B and 35B-A3B (MoE). Based on the FlagOS unified multi-chip software stack, the Zhongzhi FlagOS community completed day-0 cross-chip adaptation covering 12 platforms: T-Head, NVIDIA, Huawei Ascend, Hygon, Kunlunxin, MetaX, Moore Threads, Tsingmicro, Iluvatar CoreX, Sunrise, Mac (M5 Pro), and CIX P1. Model images are now available on ModelScope and HuggingFace simultaneously. This adaptation extends both model variants to ARM edge CPU platforms, enabling viable deployment of multimodal understanding on both data-center and end-user devices. The…