Abstract: High-quality multi-omics data generation for comprehensive molecular characterization demands stringent standards of robustness, reproducibility and time-efficiency in sample-preparation workflows. However, current mainstream methodologies in proteomics and metabolomics sample processing frequently compromise analytical depth to accelerate throughput, or necessitate discrete and independent pipelines for proteome and metabolome extraction, which critically limits the parallel multi-omics processing of scarce, low-input or clinically precious biological samples. To address this long-standing technical gap and develop an integrated sample preparation strategy, a methanol-mediated, multi-membrane integrated filtration device for the rapid parallel preparation of proteome and metabolome samples, named methanol-mediated multi-omics via filter (3M-Filter), was developed in this study. The core 3M-Filter workflow relies on methanol-induced protein precipitation and immobilization on stacked functional membrane layers, while simultaneously enabling efficient solvent-phase collection of unbound small-molecule metabolites. This innovative design obviates the need for ultrasonic cell lysis, thus not only reducing total sample processing time but also mitigating the risk of exogenous contamination in downstream analyses. Systematic validation experiments, including sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), were conducted to verify the consistent performance of 3M-Filter in efficient protein capture and synchronous metabolite recovery from heterogeneous biological matrices, including cultured cells, solid tissues and biofluids. Further benchmark evaluations were conducted using HeLa cells as the model sample with identical initial protein inputs, in direct comparison with three mainstream sample preparation methods of traditional in-solution digestion, filter-aided sample preparation (FASP), and single-pot solid-phase-enhanced sample preparation (SP3). This study demonstrated that 3M-Filter achieved a superior depth of protein and peptide identifications, enhanced reproducibility across technical replicates, higher quantitative accuracy, and improved tryptic digestion efficiency compared with all three comparator workflows. Additionally, the 3M-Filter strategy exhibited exceptional throughput advantages and maintained stable analytical performance for ultra-low-input samples containing as few as 5 000 cells. Compared with conventional lysis-buffer-based protein extraction protocols, 3M-Filter yielded significantly increased numbers of identified proteins and peptides with elevated quantitative precision, while remarkably suppressing the incidence of oxidative side-chain modifications in proteins and peptides. A pivotal merit of 3M-Filter is its unique capacity to support deep-coverage cellular proteome analysis while concurrently enabling high-coverage detection of endogenous small-molecule metabolites, generating more than 2 000 detectable spectral features in this experimental setting and thus realizing true integrated proteome-metabolome profiling from a single aliquot of sample. Collectively, these comprehensive findings confirm that 3M-Filter is a rapid, reliable and scalable sample-preparation approach that retains high proteomic depth and quantitative fidelity, while facilitating extensive metabolomic characterization without additional sample consumption. Consequently, 3M-Filter is uniquely well adapted for multi-omics sample processing of limited or clinically valuable specimens, and further represents a practical, effective and novel alternative for large-scale cohort studies that require high-quality, parallel proteomic and metabolomic measurements from minimal sample input.