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.
Analyzed 2021–2025 growth of open-source multimodal models like LLaVA, CLIP, and CogVLM.
Compared AI gateway costs for Llama 4 Scout using 1M input/output tokens.
Benchmarked AI gateways with 50 short and long prompts, successful runs only.
Benchmarked 24 LLMs on converting questions to SQL, assessing accuracy and common errors.
LLM Inference Engines Benchmark
Compare BF16, FP8, INT8 and INT4 precision formats in terms of throughput, memory efficiency, accuracy, and cost.
Compare LLMs' bias rates
Compare LLMs' visual reasoning abilities
