The author tests four AI tools — Codex, Claude Code, OpenCode, and Hermes — against a real-world task of managing 20 client follow-ups, evaluating batch processing, local file access, memory retention, pricing, and security to help users choose the best fit for their workflow.
The author prompts six recent large language models to create a web‑based Gomoku game and compares the results across four dimensions—AI opponent, execution method, visual design, and engineering rigor—revealing that Opus 5 and gpt‑5.6‑sol deliver the most complete solutions while deepseek‑v4‑pro and glm‑5.2 excel at quick, single‑file prototypes, and MiniMax‑M3, despite its polished UI, fails at human‑vs‑AI play.
After DeepSeek fully launched its image‑recognition mode, a hands‑on test revealed that while the model can spot well‑known figures like Huang Renxun, it misreads text, fails on Chinese handwriting, cannot recognize its CEO Liang Wenfeng, and lags behind Gemini, GPT 5.5 and Claude in music‑theory reasoning.
This article compares OpenAI's GPT-4.5 and GPT-4o across performance, speed, factual accuracy, hallucination rates, emotional intelligence, computing costs, and real‑world use cases, helping readers decide which model best fits their needs.
This article compares the open‑source large language models Falcon 180B and Meta’s Llama 2, detailing their parameter sizes, training data, licensing, variants, infrastructure, language support, and safety policies, while providing links to official resources and a side‑by‑side feature table.
The article reviews Baidu’s newly launched Ernie Bot, a multimodal large language model, comparing its literary, business, mathematical, Chinese comprehension, and multimodal abilities with GPT‑4, while detailing the underlying technologies, knowledge‑enhancement techniques, and deployment strategy behind the model.
