Şevval Alper
Şevval is an AI researcher at AIMultiple. She has previous research experience in pseudorandom number generation using chaotic systems.
Research interests
Şevval focuses on AI coding tools, AI agents, and quantum technologies.
She is part of the AIMultiple benchmark team, conducting assessments and providing insights to help readers understand various emerging technologies and their applications.
Professional experience
She contributed to organizing and guiding participants in three “CERN International Masterclasses - hands-on particle physics” events in Türkiye, working alongside faculty to facilitate learning.
Education
Şevval holds a Bachelor's degree in Physics from Middle East Technical University.
Latest Articles from Şevval
AI Reasoning Benchmark: MathR-Eval
We evaluated eight leading LLMs using a 100-question mathematical reasoning dataset, MathR-Eval, to measure how well each model solves structured, logic-based math problems. All models were tested zero-shot, with identical prompts and standardized answer checking. This enabled us to measure pure reasoning accuracy and compare both reasoning and non-reasoning models under the same conditions.
OCR Benchmark: Text Extraction / Capture Accuracy
OCR accuracy is critical for many document processing tasks and SOTA multi-modal LLMs are now offering an alternative to OCR.
MCP Benchmark: Top MCP Servers for Web Access
We benchmarked 8 MCP servers across web search, extraction, and browser automation by running 4 different tasks 5 times each. We also tested scalability with 250 concurrent AI agents.
LLM Parameters: GPT-5 High, Medium, Low and Minimal
New LLMs, such as OpenAI’s GPT-5 family, come in different versions (e.g., GPT-5, GPT-5-mini, and GPT-5-nano) and with various parameter settings, including high, medium, low, and minimal. Below, we explore the differences between these model versions by gathering their benchmark performance and the costs to run the benchmarks. Price vs.
Screenshot to Code: Lovable vs v0 vs Bolt
During my 20 years as a software developer, I led many front-end teams in developing pages based on designs that were inspired by screenshots. Designs can be transferred to code using AI tools.
AGI Benchmark: Can AI Generate Economic Value
AI will have its greatest impact when AI systems start to create economic value autonomously. We benchmarked whether frontier models can generate economic value. We prompted them to build a new digital application (e.g., website or mobile app) that can be monetized with a SaaS or advertising-based model.
Best AI Code Editor: Cursor vs Windsurf vs Replit
Making an app without coding skills is highly trending right now. But can these tools successfully build and deploy an app? To answer this question, we spent three days testing the following agentic IDEs/AI coding tools: Claude Code, Cline, Cursor, Windsurf and Replit Agent.
E-Commerce AI Video Maker Benchmark: Veo 3 vs Sora 2
Product visualization plays a crucial role in e-commerce success, yet creating high-quality product videos remains a significant challenge. Recent advancements in AI video generation technology offer promising solutions.
Speech-to-Text Benchmark: Deepgram vs. Whisper
We benchmarked the leading speech-to-text (STT) providers, focusing specifically on healthcare applications. Our benchmark used real-world examples to assess transcription accuracy in medical contexts, where precision is crucial. Benchmark results Based on both WER and CER results, GPT-4o-transcribe demonstrates the highest transcription accuracy among all evaluated speech-to-text systems.
Top 4 AI Search Engines Compared
Searching with LLMs has become a major alternative to Google search. We benchmarked the following AI search engines to see which one provides the most correct results: Benchmark results Deepseek is the leader of this benchmark, by correctly providing 57% of the data in our ground truth dataset.
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