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@merceod merceod released this 12 Jul 10:47
· 483 commits to main since this release
v0.2.0
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Learn about vigilant mode.

Highlights

  • New model family: Cosmos3 (nvidia/Cosmos3-Nano, nvidia/Cosmos3-Super) text/image/video-to-video generation, robot-action modes, and optional synchronized sound; tensor- and sequence-parallel multi-GPU serving; CUDA-graph-captured denoising; mstar serve cosmos3 / mstar serve cosmos3_super; install via pip install mstar[cosmos3] (#121)
  • PyTorch unpinned (torch>=2.9.1): the sgl-kernel dependency was replaced by a vendored, JIT-compiled CUDA kernel for the fused-MoE align op (#157)
  • Per-request profiling support (#144)
  • Piecewise CUDA-graph runner made model-agnostic (#154)
  • In-flight requests abort when the client disconnects (#136)

Fixes

  • KV-cache engine no longer leaks per-request submodule state (#146)
  • Qwen3-Omni: Talker TTS embedding dtype mismatch (#138); flashinfer floor fixes the Talker sampler on graph-captured decode (#139)
  • Submodule params allocate in the autocast dtype, avoiding fp32 weight-load OOM (#120)
  • numba>=0.61 pin avoids an incompatible llvmlite (#152)
  • food101 image-to-image benchmark used captioning prompts instead of edit prompts (#158)
  • Setup and testing fixes (#116); torch.compile dynamic-param fix (#117); docs and README updates (#113, #114, #118, #122, #133, #134, #153)

Install notes

  • New .[cosmos3] extra. Its fa3-fwd fast-path wheel is ABI-tied to your torch/CUDA build; on a mismatch the engine logs a warning and serves on the paged FlashInfer backend (see docs/models.rst).
  • ninja is now required for Qwen3-Omni (first-use JIT build of the MoE align kernel; replaces sgl-kernel).
  • flash-attn prebuilt wheels top out at torch 2.10 - on newer torch, build from source (see docs/installation.rst).
  • torchcodec is no longer pinned so keep its version in lockstep with your torch.

Full changelog: v0.1.0...v0.2.0

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