Artificial Intelligence
Explore practical insights, research, and benchmarks on artificial intelligence, including generative AI, large language models, RAG, governance frameworks, MLOps practices, and AI hardware. Gain an understanding of key tools, implementation strategies, and enterprise use cases shaping the AI landscape.
Explore Artificial Intelligence
DGX Spark vs Mac Studio & Halo: Benchmarks & Alternatives
NVIDIA’s DGX Spark entered the desktop AI market in 2025 at $4,699, positioning itself as a “desktop AI supercomputer”. It packs 128GB of unified memory and promises one petaflop of FP4 AI performance in a Mac Mini-sized chassis. See the benchmark results on value and performance compared to alternatives: When comparing systems on the demanding…
GPU Software for AI: CUDA vs. ROCm in 2026
Raw hardware specifications tell half the story in GPU computing. To measure real-world AI performance, we ran 52 distinct tests comparing AMD’s MI300X with NVIDIA’s H100, H200, and B200 across multi-GPU and high-concurrency scenarios. While AMD’s MI300X boasts 1,307 TFLOPS compared to NVIDIA’s H100/H200 at 990 TFLOPS, a 32% theoretical advantage, real-world performance is a…
Top 8 Open Source AI Coding Agents
In prior evaluations, we benchmarked both open-source and proprietary Agentic CLIs, focusing on their performance in web development tasks, and some open-source agents performed as successfully as the paid options. Therefore, we also listed the top open-source coding agents for users with privacy concerns. For methodology, see the AI coding benchmark. For more details about…
Embedding Models: OpenAI vs Gemini vs Voyage
We benchmarked 15 English text-embedding models and a BM25 baseline on over 500 manually curated queries across three retrieval domains: legal contracts (CUAD), customer support (IBM TechQA), and healthcare (MedRAG PubMed). Voyage-3.5 ranks first overall. Perplexity Embed V1 0.6b reaches the upper-mid tier at the lowest price point in our benchmark. nDCG@3: Normalized discounted cumulative…
RAG Frameworks: LangChain vs LangGraph vs LlamaIndex
We benchmarked 5 RAG frameworks: LangChain, LangGraph, LlamaIndex, Haystack, and DSPy, by building the same agentic RAG workflow with standardized components: identical models (GPT-4.1-mini), embeddings (BGE-small), retriever (Qdrant), and tools (Tavily web search). This isolates each framework’s true overhead and token efficiency. The benchmark consisted of 100 queries, with each framework running the full set…
Top 15 AI Excel Tools Benchmarked
79% of companies claim to have adopted AI agents, and two-thirds of those users say these agents have boosted productivity in measurable ways.20 We test and compare 15 AI Excel tools to see how they handle real spreadsheet work. We ran two benchmarks. Quadratic and GPT for Excel scored the highest. Summary of other results:…
Test Automation Documentation with Best Practices
Test automation is vital for ensuring the quality and reliability of applications in software testing and development. Businesses and QA teams are transitioning from manual testing to automation testing as it can: What often goes overlooked is the role of effective documentation in maximizing the benefits of test automation. We explore the importance of test…
Compare 9 Large Language Models in Healthcare
We benchmarked 9 LLMs using the MedQA dataset, a graduate-level clinical exam benchmark derived from USMLE questions. Each model answered the same multiple-choice clinical scenarios using a standardized prompt, enabling direct comparison of accuracy. We also recorded latency per question by dividing total runtime by the number of MedQA items completed. Benchmark methodology: This benchmark…
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. We benchmarked leading OCR services in DeltOCR Bench to identify their accuracy levels in different document types: The full names of the above products and their versions in use as of November 2025 are listed…
Reranker Benchmark: Top 8 Models Compared
We benchmarked 8 reranker models on ~145k English Amazon reviews to measure how much a reranking stage improves dense retrieval. We retrieved top-100 candidates with multilingual-e5-base, reranked them with each model, and evaluated the top-10 results against 300 queries, each referencing concrete details from its source review. The best reranker lifted Hit@1 from 62.67% to…