LLM Use Cases, Analyses & Benchmarks
LLMs are AI systems trained on vast text data to understand, generate, and manipulate human language for business tasks. We benchmark performance, use cases, cost analyses, deployment options, and best practices to guide enterprise LLM adoption.
Explore LLM Use Cases, Analyses & Benchmarks
Compare Multimodal AI Models on Visual Reasoning
We benchmarked 15 leading multimodal AI models on visual reasoning using 200 visual-based questions. The evaluation consisted of two tracks: 100 chart understanding questions testing data visualization interpretation, and 100 visual logic questions assessing pattern recognition and spatial reasoning. Each question was run 5 times to ensure consistent and reliable results.
50+ ChatGPT Use Cases with Real Life Examples
ChatGPT reached approximately 1 billion weekly active users in early 2026 roughly 10% of the world’s population. OpenAI surpassed $20 billion in annual revenue for 2025, confirmed by CFO Sarah Friar. OpenAI and Harvard economist David Deming analyzed 1.5 million conversations to find out.
The Future of Large Language Models
See the future of large language models by delving into promising approaches, such as self-training, fact-checking, and sparse expertise that could address LLM limitations. Success rate comparison of LLM’s Claude 4.5 Sonnet and GPT-5.2 had the highest overall scores with the most consistent results across both API logic and UI integration. Gemini 3.
LLM VRAM Calculator for Self-Hosting
The use of LLMs has become inevitable, but relying solely on cloud-based APIs can be limiting due to cost, reliance on third parties, and potential privacy concerns. That’s where self-hosting an LLM for inference (also called on-premises LLM hosting or on-prem LLM hosting) comes in.
Audience Simulation: Can LLMs Predict Human Behavior?
In marketing, evaluating how accurately LLMs predict human behavior is crucial for assessing their effectiveness in anticipating audience needs and recognizing the risks of misalignment, ineffective communication, or unintended influence.
LCMs: From LLM Tokenization to Concept-level Representation
Large concept models (LCMs), as introduced by Meta in their work on “Large Concept Models,” represent a fundamental shift away from token-based prediction toward concept-level representation.
ChatGPT for Customer Service: Top 10 Use Cases
ChatGPT has moved from novelty to infrastructure in customer service. Companies are using it to cut response times, handle volume their teams can’t absorb, and reduce the cost of routine interactions. But results vary sharply depending on how it’s implemented. OpenAI launched GPT-5.
Benchmark of 39 LLMs in Finance: Claude Opus 4.7, Gemini 3.1 Pro & More
We evaluated 39 LLMs in finance on 238 hard questions from the FinanceReasoning benchmark to identify which models excel at complex financial reasoning tasks like statement analysis, forecasting, and ratio calculations. LLM finance benchmark overview We evaluated LLMs on 238 hard questions from the FinanceReasoning benchmark (Tang et al.).
LLM Market Share: Compare Usage & Adoption
We analyzed LLM market share by combining usage-based data and web visit estimates to show how demand for large language models is distributed across AI labs and AI applications: LLM market share comparison by country Read the methodology to see how we measured and calculated these results.
Text-to-SQL: Comparison of LLM Accuracy
I have relied on SQL for data analysis for 18 years, beginning in my days as a consultant. Translating natural-language questions into SQL makes data more accessible, allowing anyone, even those without technical skills, to work directly with databases.