Nazlı Şipi
She is also part of the benchmark team, focusing on large language models (LLMs), AI agents, and agentic frameworks.
Nazlı holds a Master’s degree in Business Analytics from the University of Denver.
Latest Articles from Nazlı
Best Zillow Scraper APIs Compared: Performance review
We benchmarked best five web scraping providers on Zillow, one of the top real estate domains, running over 1,250 scrape requests across all providers. Each provider received an identical set of property listing URLs and was evaluated on completion time, success rate, and the number of structured data fields returned per listing.
Best Airbnb Scrapers: Bright Data, Apify & Oxylabs
We tested six web scraping providers on Airbnb, sending a total of 1,500 scrape requests across all providers. Each provider was given the same set of vacation rental listing URLs and measured on completion time, success rate, and available metadata fields per listing.
5 Best Google Maps Scraper APIs in 2026: Tested & Ranked
To find the best Google Maps scraper, we benchmarked the top providers, Apify, Oxylabs, Octoparse, and SerpApi by running 100 searches for each. We tested 10 categories and analyzed 4,000 business listings. We also verified phone numbers and reviews to ensure the data is actually useful for your lead generation.
Agentic LLM Benchmark: Top 13 LLMs Compared
We benchmarked 13 LLMs across 10 software development tasks by using an agentic CLI tool. We executed ~300 automated validation steps per model to measure performance across both API and UI layers. Agentic LLM benchmark results Success rate comparison Claude 4.5 Sonnet and GPT-5.
Vision Language Models Compared to Image Recognition
Can advanced Vision Language Models (VLMs) replace traditional image recognition models? To find out, we benchmarked 16 leading models across three paradigms: traditional CNNs (ResNet, EfficientNet), VLMs ( such as GPT-4.1, Gemini 2.5), and Cloud APIs (AWS, Google, Azure).
Top 7 Video Scrapers in 2026: Tested & Ranked
Major video-sharing networks are highly dynamic environments that present significant challenges for automated data extraction. Technical hurdles, such as the prevalence of infinite-scrolling layouts in short-form video feeds, often cause standard scrapers to fail to consistently retrieve data.
2026 Web Crawler Benchmark to Feed Websites to AI
We benchmarked four crawl APIs across three domains of varying difficulty at three max depth levels (5, 10, 20) with a 1,000-page limit, measuring crawl coverage, execution time, link discovery, markdown link quality, and title extraction accuracy. If you aim to: Web crawlers benchmark You can read our benchmark methodology.
Top 6 LLM Scrapers in 2026
We ran a benchmark to compare how top LLM scraper providers like Bright Data, Oxylabs, and Apify perform with models such as ChatGPT, Gemini, Perplexity, and Google AI Mode. To ensure reliable results, we ran 1,000 tests per provider with each prompt repeated 10 times for consistency. The top-performing provider is detailed below.
Top 5 Open-Source Agentic AI Frameworks in 2026
We benchmarked 4 popular open-source agentic frameworks across 2,000 runs (5 tasks, 100 runs each per framework), measuring end-to-end latency, token consumption, and architectural differences. Agentic AI frameworks benchmark We examined how the frameworks themselves influence agent behavior and the resulting impact on latency and token consumption.
Multi-Agent Frameworks Benchmark: Challenges & Strengths
Multi-agent systems use specialized agents working together to solve complex tasks. A key challenge: does performance degrade as more agents and tools are added, or can orchestration mechanisms handle the growing complexity efficiently? We benchmarked 5 agentic frameworks across 750 runs with three tasks.
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