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.
Github Stars of Open-Source Multimodal Models
Analyzed 2021–2025 growth of open-source multimodal models like LLaVA, CLIP, and CogVLM.
Cost comparison of AI gateways
Compared AI gateway costs for Llama 4 Scout using 1M input/output tokens.
First token latency comparison of AI gateways
Benchmarked AI gateways with 50 short and long prompts, successful runs only.
Text-to-SQL Benchmark
Benchmarked 24 LLMs on converting questions to SQL, assessing accuracy and common errors.
Explore LLM Use Cases, Analyses & Benchmarks
Compare 10+ LLMs in Healthcare
Large language models (LLMs) are increasingly being applied in healthcare to support clinical tasks such as medical question answering, patient communication, and summarizing medical records.
Context Engineering: Maximize LLM Grounding & Accuracy
LLMs often struggle with raw, unstructured data such as email threads or technical documents, leading to factual errors and weak reasoning. We benchmarked systematic context engineering and achieved up to +13.0% improvement in task accuracy, confirming that structured context is key to enhancing performance in complex tasks.
Compare Top 13 LLM Orchestration Frameworks
Leveraging multiple LLMs concurrently demands significant computational resources, driving up costs and introducing latency challenges. In the evolving landscape of AI, efficient LLM orchestration is essential for optimizing performance while minimizing expenses. Explore key strategies and tools for managing multiple LLMs effectively.
Benchmark of 30 Finance LLMs: GPT-5, Gemini 2.5 Pro & more
Large language models (LLMs) are transforming finance by automating complex tasks such as risk assessment, fraud detection, customer support, and financial analysis. Benchmarking finance LLM can help identify the most reliable and effective solutions.
LLM Pricing: Top 15+ Providers Compared
We analyzed 15+ LLMs and their pricing and performance. LLM API pricing can be complex and depends on your preferred usage. If you plan to use: Hover over model names to see their full names and over headers to see explanations about the columns.
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.
Large Multimodal Models (LMMs) vs LLMs
We evaluated the performance of Large Multimodal Models (LMMs) in financial reasoning tasks using a carefully selected dataset. By analyzing a subset of high-quality financial samples, we assess the models’ capabilities in processing and reasoning with multimodal data in the financial domain. The methodology section provides detailed insights into the dataset and evaluation framework employed.
LLM Parameters: GPT-5 High, Medium, Low and Minimal
New LLMs, such as OpenAI’s GPT-5 family, come with different versions (e.g., GPT-5, GPT-5-mini, and GPT-5-nano) and various parameters, including high, medium, low, and minimal. Below, we explore the differences between these versions of the models by gathering their benchmark performances and the costs to run these benchmarks. Price vs.
LLM Latency Benchmark by Use Cases
The effectiveness of large language models (LLMs) is determined not only by their accuracy and capabilities but also by the speed at which they engage with users. We benchmarked the performance of leading language models across various use cases, measuring their responsiveness to user input.
Top 5 AI Gateways for OpenAI: OpenRouter Alternatives
The growing number of LLM providers creates significant API management hurdles. AI gateways address this complexity by acting as a central routing point, enabling developers to interact with multiple providers through a single, unified API, thereby simplifying development and maintenance.