LLMs
LLM Latency Benchmark by Use Cases in 2025
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 how quickly they respond to user input.
Text-to-SQL: Comparison of LLM Accuracy in 2025
I have been relying on SQL for data analysis for 18 years, beginning with 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.
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.
LLM VRAM Calculator for Self-Hosting in 2025
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.
LLM Pricing: Top 15+ Providers Compared in 2025
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: [data_table slug=llm-prices] Hover over model names to see their full names and over headers to see explanations about the columns.
Compare Top 11 LLM Orchestration Frameworks in 2025
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.
Compare Top 20 LLM Security Tools & Free Frameworks
Chevrolet of Watsonville, a car dealership, introduced a ChatGPT-based chatbot on their website. However, the chatbot falsely advertised a car for $1, potentially leading to legal consequences and resulting in a substantial bill for Chevrolet. Incidents like these highlight the importance of implementing security measures to LLM applications.
Cloud LLM vs Local LLMs: 3 Real-Life examples & benefits
In 2025, Cloud LLMs and Local LLMs are transforming business operations with unique advantages. Cloud LLMs, powered by advanced models like Grok 3, o3, and GPT-4.1, offer exceptional scalability and accessibility. Conversely, Local LLMs, driven by open-source models such as Qwen 3, Llama 4, and DeepSeek R1, ensure superior privacy and customization.
Large Multimodal Models (LMMs) vs LLMs in 2025
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 Data Guide & 6 Methods of Collection in 2025
In the expanding AI and generative AI market (Figure 1), large language models (LLMs) have emerged as pivotal. These models empower machines to generate human-like content, heavily reliant on quality data. Here, we present a guide for business leaders on accessing and managing LLM data, offering insights into collection methods and data collection services.