Code equivalence analysis is a critical problem in software engineering. In this paper, we focus on assessing if two code segments exhibit diverging behaviors. While symbolic analysis, exemplified by techniques like differential symbolic execution and impacted summaries, has been employed for equivalence analysis, it faces challenges due to limitations of symbolic execution, producing inconclusive results in many cases. To mitigate these limitations, we introduce a hybrid approach that integrates symbolic analysis with differential fuzzing. Differential fuzzing, although unable to prove equivalence like symbolic analysis, is valuable in identifying non-equivalent instances quickly. Our proposed hybrid approach leverages the strengths of symbolic reasoning and fuzzing within a single workflow for more effective analysis. The contributions of this paper include the introduction of a hybrid equivalence/non-equivalence testing approach, multiple heuristics for hybrid analysis, and differential fuzzing. Our experimental evaluation on multiple benchmarks including EQBench and ARDiff, demonstrates that our proposed hybrid techniques can prove equivalence/non-equivalence for 28.52% more cases taking 43.21% less time on average compared to state-of-the-art symbolic execution based techniques.