LingBot-World-v2 14B causal-fast — GGUF (8GB-VRAM ready)

WORK IN PROGRESS!

GGUF quantizations of robbyant/lingbot-world-v2-14b-causal-fast for ComfyUI_Rebels_LingBotWorld — an action-controlled world model running on consumer GPUs (tested: RTX 3070 8GB / 16GB RAM).

You author a camera/movement track (or type one into the Action Builder node); the model renders the video that track produces from your start image, with genuine action following. Offline generation, chunked causal sampling, 4 distilled steps per chunk.

Files

FileNotesLingBot-World-14B-Q4_K_S.gguf (~11.7GB)tested tier; Q5-bumped v-projections keep effective bpw ~6.7other tiers (Q4_K_M…Q8_0)quality ladder; RAM-streamed, VRAM use is unchanged

Also required: Wan2.1_VAE.pth, a UMT5-XXL GGUF encoder (loads via ComfyUI-GGUF CLIPLoader, type wan)

Settings that matter (8GB)

• Resolution preset 256×448 (default) or 320×544; world-memory window 6+2

• The KV cache is the world memory: it scales with window × resolution (upstream 18+6 @ 480×832 ≈ 21GB — does not fit consumer cards; the sampler pre-checks and refuses instead of hanging)

• frame_num 4n+1; start at 21; export 16 fps

License

CC BY-NC-SA 4.0 (inherited from upstream): non-commercial, attribution, share-alike. Quantization is a format conversion only. Quants + nodes by RealRebelAI.