#ai-models
10 articles exploring ai-models. Expert insights and analysis from our editorial team.
Articles
AI Diagnostics in 2026: Where Machines Now Outperform Radiologists
AI diagnostic tools demonstrably outperform human radiologists in several imaging modalities—yet fewer than 10% of U.S. hospitals have deployed them in clinical use. Here's the evidence, the gaps, and what's actually blocking adoption.
Fish-Speech: The Open-Source TTS Model That's Threatening ElevenLabs
Fish Audio's S2 model reached SOTA benchmarks in March 2026 with sub-100ms latency, 80+ languages, and open-sourced weights—directly challenging ElevenLabs' commercial dominance while exposing the real costs of 'free' voice AI.
NousResearch's Hermes-Agent: The AI That Learns Your Preferences Over Time
Hermes-Agent from NousResearch is an open-source autonomous agent that builds a persistent model of each user—tracking preferences, writing its own skills, and getting measurably more capable the longer it runs.
Claude's Web Search Changes Everything for AI Research
Anthropic's web search integration removes the static knowledge ceiling from Claude, enabling real-time retrieval directly inside the reasoning loop—with verifiable citations, domain filtering, and a new dynamic filtering layer that cuts token use by 24% while improving accuracy by 11%.
DeepSeek V3/R1: How Chinese Engineers Matched GPT-4 for $6 Million
DeepSeek's V3 and R1 models match GPT-4-class performance using a fraction of the compute through architectural innovations in Mixture of Experts, attention compression, and reinforcement learning—demonstrating that training efficiency may matter more than raw hardware scale.
Gemini 2.0 Pro's 2 Million Token Context: What Can You Actually Do With It?
Google's Gemini 2.0 Pro Experimental ships with a 2 million token context window—the largest among production-accessible models. Here's what practitioners have discovered works, what doesn't, and what the hard limits are.
Gemini 3.1 Pro: Google's New Reasoning Model Explained
Gemini 3.1 Pro is Google's latest reasoning-focused AI model, achieving 77.1% on ARC-AGI-2 benchmarks—more than double the performance of its predecessor. Here's how it compares to Claude and GPT.
Kimi Claw: Moonshot AI's Answer to Claude and ChatGPT
Moonshot AI's Kimi series has emerged as China's leading open-source AI challenger, offering trillion-parameter models with advanced agentic capabilities at a fraction of Western competitors' costs.
Two Different Tricks for Fast LLM Inference: Speeding Up AI Responses
Speculative decoding and efficient memory management through PagedAttention are two proven techniques that accelerate LLM inference by 2-24x without sacrificing output quality, enabling production deployments at scale.
The Best AI Models for OpenClaw in 2026
A comprehensive guide to selecting the right LLM for your OpenClaw workflows, covering coding, writing, reasoning, and cost-effective options.