<p>Summarization of web content plays a crucial role in making vast amounts of online information more accessible and digestible for users, particularly individuals with visual impairments. It helps condense lengthy articles into concise summaries, enabling quicker understanding and easier navigation through digital content. In this paper, we present a Chrome extension web application designed to summarize web content for individuals with visual impairments. The system utilizes four locally deployable LLMs: Llama 3.1, Phi 3, Gemma 2, and Mistral, which generate summaries from web pages. To ensure that the best summary is provided, a weighted sum approach was implemented to evaluate summaries across 42 news articles from seven BBC News domains. Gemma 2 emerged as the top model, achieving the highest weighted sum score of 0.585, delivering the best summaries in 17 out of 42 cases, and excelling in readability with the highest FRE score of 52.53 and lowest FKGL score of 10.08. It produced concise summaries with an average word count of 70.19, outperforming other models. A usability study with visually impaired users highlighted Gemma 2 as the preferred model (35.2%), followed by Llama 3.1 (28.7%) and Mistral (26.2%). The system received an effectiveness rating of 4.18/5, with 81.8% of users rating it 4 or higher, reflecting high satisfaction. A comparison with tools like ’TLDR This’ and ’AI Summarizer’ showed WEBSumm’s superior accessibility and readability, making it a more inclusive solution. The results highlight the effectiveness of the weighted sum method in delivering high-quality, accessible summaries with enhanced usability. The proposed model outperforms existing tools in readability, coherence, and accessibility, making it more suitable for diverse user needs. This work uniquely contributes to web accessibility, enabling persons with visual impairments to navigate and understand web content with ease.</p>