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We present the CUHKSZ Team submission to the IWSLT 2026 Simultaneous Speech Translation evaluation, targeting the main and Extra Context tracks for English→Chinese, German on unsegmented speech. Our system is built upon Qwen3-Omni-30B-A3B, a natively aligned audio-text LLM. Under the Constrained condition, we apply LoRA adaptation exclusively to the LLM. Specifically, we construct syntax-aware, chunk-aligned supervision from existing ASR corpora, using Qwen3-30B-Instruct to synthesize target translations. This enables the model to internalize the simultaneous read/write policy by autonomously predicting <wait> tokens at semantically incomplete boundaries. With the policy internalized, execution is delegated to a lightweight streaming agent served via vLLM. This agent feeds audio in fixed chunks, manages a bounded dialogue history, and enforces strict emission controls to minimize computation-aware delay. For the sub-track, contextual priors are dynamically injected into the prompt. On the official dev set, our 0–2 s latency regime submissions achieve 40.5 BLEU (1.95 s) for En→Zh and 27.7 BLEU (1.72 s) for En→De. In the 2–4 s regime, performance scales to 42.1 BLEU (2.16 s) and 30.5 BLEU (2.29 s) respectively.