Background: The HIV-1 proviral reservoir is incredibly stable, even while undergoing antiretroviral therapy, and is seen as the major barrier to HIV-1 eradication. Identifying and comprehensively characterizing this reservoir will be critical to achieving an HIV cure. Historically, this has been a tedious and labor intensive process, requiring high-replicate single-genome amplification reactions, or overlapping amplicons that are then reconstructed into full-length genomes by algorithmic imputation. Here, we present a deep sequencing and analysis method able to determine the exact identity and relative abundances of near-full-length HIV genomes from samples containing mixtures of genomes without shearing or complex bioinformatic reconstruction. Methods: We generated clonal near-full-length (~9 kb) amplicons derived from single genome amplification (SGA) of primary proviral isolates or PCR of well-documented control strains. These clonal products were mixed at various abundances and sequenced as near-full-length (~9 kb) amplicons without shearing. Each mixture yielded many near-full-length HIV-1 reads. Mathematical analysis techniques resolved the complex mixture of reads into estimates of distinct near-full-length viral genomes with their relative abundances. Results: Single Molecule, Real-Time (SMRT) Sequencing data contained near-full-length (~9 kb) continuous reads for each sample including some runs with greater than 10,000 near-full-length-genome reads in a three-hour sequencing run. Our methods correctly recapitulated exactly the originating genomes at a single-base resolution and their relative abundances in both mixtures of clonal controls and SGAs, and these results were validated using independent sequencing methods. Correct resolution was achieved even when genomes differed only by a single base. Minor abundances of 5% were reliably detected. Conclusions: SMRT Sequencing yields long-read sequencing results from individual DNA molecules, a rapid time-to-result. The single-molecule, full-length nature of this sequencing method allows us to estimate variant subspecies and relative abundances with single-nucleotide resolution. This method allows for reference-agnostic and cost-effective full-genome sequencing of HIV-1, which could both further our understanding of latent infection and develop novel and improved tools for quantifying HIV provirus, which will be critical to cure HIV.