a quantized vision-language framework for conversational crop health diagnosis on resource-constrained edge hardware, with an offline chat interface — no cloud connectivity needed for a grower to ask questions and get diagnoses and management guidance. Validated on two VLM backbones and deployed on an NVIDIA Jetson AGX Orin: 4-bit AWQ quantization retains 98.6% of full-precision answer quality while cutting the 2B backbone's weight memory by 49% (2.01 GiB in its most compact form, first token in about 0.12s). Directly adjacent to the AgriMesh lane.