We present constrained WMT 2026 submissions for low-resource Northeastern Indian languages using NLLB-200 Distilled 1.3B with multilingual LoRA adapters trained only on the official organizer-provided parallel data. The adapted systems improve over the submitted baselines for both Mizo directions and Bengali-script Manipuri→English, but show substantial variation across languages and directions. We further manually analyze approximately 100 Indic→English outputs and validate the systems on WMT 2025 data, highlighting generation artifacts and the challenges of parameter-efficient adaptation across languages, scripts, and translation directions.