Modern sequencing pipelines routinely produce billions of reads, yet the dominant storage formats (FASTQ and FASTA) are text-based and sequential, making high-throughput parsing a persistent bottleneck in bioinformatics. Their regular, line-oriented structure makes them well-suited to SIMD vectorization, but existing libraries do not fully exploit it. We present vectorized algorithms for high-throughput FASTA/Q parsing, with on-the-fly handling of non-ACTG characters and built-in bitpacking of DNA sequences into multiple compact representations. The parsing logic is expressed as a finite state machine, compiled into efficient SIMD programs targeting both x86 and ARM CPUs. These algorithms are implemented in Helicase, a Rust library exposing a tunable interface that retrieves only caller-requested fields, minimizing unnecessary work. Exhaustive benchmarks across a wide range of CPUs show that Helicase meets or exceeds the throughput of all evaluated state-of-the-art libraries, making it the fastest general-purpose FASTA/Q parser to our knowledge. Availability: https://github.com/imartayan/helicase