Point-of-care diagnostics often use isothermal nucleic acid amplification for qualitative detection of pathogens in low-resource healthcare settings but lack sufficient precision for quantitative applications such as HIV viral load monitoring. Although viral load (VL) monitoring is an essential component of HIV treatment, commercially available tests rely on relatively high-resource chemistries like real-time polymerase chain reaction and are thus used on an infrequent basis for millions of people living with HIV in low-income countries. To address the constraints of low-resource settings on nucleic acid quantification, we describe a recombinase polymerase amplification and lateral flow detection approach that quantifies HIV-1 DNA or RNA by comparison to a competitive internal amplification control (IAC) of a known copy number, which may be set to any useful threshold (in our case, a clinically relevant threshold for HIV treatment failure). The IAC is designed to amplify alongside the HIV target with a similar efficiency, allowing for normalization of the assay to variation or inhibition and enabling an endpoint readout that is compatible with commercially available kits for nucleic acid lateral flow detection and interpretable with minimal instrumentation or by the naked eye. We find that this approach can reliably differentiate ≤600 or ≥1400 copies of HIV DNA from a 1000-copy threshold when lateral flow strips are imaged with a conventional office scanner and analyzed with free densitometry software. We further demonstrate a user-friendly adaptation of this analysis to process cell phone photographs with an automated script. Alternatively, we show via a survey that 21 minimally trained volunteers could reliably resolve ≥10-fold (log10) differences of HIV DNA or RNA by naked eye interpretation of lateral flow results. This amplification and detection workflow requires minimal instrumentation, takes just 30 min to complete, and when combined with a suitable sample preparation method, may enable HIV VL testing while the patient waits or a self-test, which has the potential to improve care. This approach may be adapted for other applications that require quantitative analysis of a nucleic acid target in low-resource settings.