This work presents a hardware-efficient and fully parallelizable decoder for quantum LDPC codes that leverages belief propagation (BP) with a speculative post-processing strategy inspired by classical Chase decoding algorithm. By monitoring bit-level oscillation patterns during BP, our method identifies unreliable bits and generates multiple candidate vectors to selectively flip syndromes. Each modified syndrome is then decoded independently using short-depth BP, a process we refer to as BP-SF (syndrome flip). This design eliminates the need for costly Gaussian elimination used in the current BP-OSD approaches. Our implementation achieves logical error rates comparable to or better than BP-OSD while offering significantly lower latency due to its high degree of parallelism for a variety of bivariate bicycle codes. Evaluation on the $\llbracket 144,12,12\rrbracket$ bivariate bicycle code shows that the proposed decoder reduces average latency to approximately $70%$ of BP-OSD. When post-processing is parallelized the average latency is further down to $55%$ compared with the single process implementation, with maximum latency reaching as low as $18%$. These advantages make it particularly well-suited for real-time and resource-constrained quantum error correction systems.