Second GPU pass (distilled + huge dense, 2-wide). 5 verified end-to-end with real
weights; CPU toy path kept green (240 passed, 2 skipped).
VERIFIED:
* matrixgame3 — mp4 (9,256,256,3), zero fixes. 6.47B, standard Wan attn (NOT
sparse-attn-blocked, like its mg2 sibling); degenerate single-clip.
* fastwan — FastWan2.2-TI2V-5B-FullAttn DMD 3-step, mp4 (17,256,256,3), zero
fixes. The FULL-ATTENTION variant has no VSA params -> the generic
Wan loader maps it cleanly (reuses WanDiT via load_id, no adapter).
* longcat — LongCat-Video-T2V 13.58B, mp4 (17,256,256,3), zero fixes, CPU
offload (~40GB peak).
* sfwan22 — Self-Forcing Wan2.2-A14B causal+MoE (2x14B), mp4 (29,288,288,3),
CPU expert offload (~80GB peak).
* lingbotworld — Wan2.2-class 2x14B camera world model, mp4 (9,256,256,3), offload
(~98GB peak transient).
BLOCKED: turbowan-i2v-a14b — SLA sparse-attn params (attn1.attn_impl.proj_l on all
40 layers of both experts) cannot load into the dense Wan build + needs the
fastvideo-kernel SLA Triton kernels (no nvcc here). Confirmed via the safetensors
header (no 60GB download). Same SLA family as turbowan-1.3b.
Fixes (own-port only): sfwan22/loop.py, lingbotworld/{card,program}.py +
torch_lingbotworld.py. pre-commit clean per-package.
SolitaryThinker
0ac5367b54