Nonprobability Web surveys using volunteer panels can provide a relatively cheap and quick alternative to traditional health and epidemiological surveys. However, concerns have been raised about their representativeness.The aim was to compare results from different Web panels with a population-based probability sample survey (n=8969 aged 18-44 years) that used computer-assisted self-interview (CASI) for sensitive behaviors, the third British National Survey of Sexual Attitudes and Lifestyles (Natsal-3).Natsal-3 questions were included on 4 nonprobability Web panel surveys (n=2000 to 2099), 2 using basic quotas based on age and sex, and 2 using modified quotas based on additional variables related to key estimates. Results for sociodemographic characteristics were compared with external benchmarks and for sexual behaviors and opinions with Natsal-3. Odds ratios (ORs) were used to express differences between the benchmark data and each survey for each variable of interest. A summary measure of survey performance was the average absolute OR across variables. Another summary measure was the number of key estimates for which the survey differed significantly (at the 5% level) from the benchmarks.For sociodemographic variables, the Web surveys were less representative of the general population than Natsal-3. For example, for men, the average absolute OR for Natsal-3 was 1.14, whereas for the Web surveys the average absolute ORs ranged from 1.86 to 2.30. For all Web surveys, approximately two-thirds of the key estimates of sexual behaviors were different from Natsal-3 and the average absolute ORs ranged from 1.32 to 1.98. Differences were appreciable even for questions asked by CASI in Natsal-3. No single Web survey performed consistently better than any other did. Modified quotas slightly improved results for men, but not for women.Consistent with studies from other countries on less sensitive topics, volunteer Web panels provided appreciably biased estimates. The differences seen with Natsal-3 CASI questions, where mode effects may be similar, suggest a selection bias in the Web surveys. The use of more complex quotas may lead to some improvement, but many estimates are still likely to differ. Volunteer Web panels are not recommended if accurate prevalence estimates for the general population are a key objective.