James Kowalski

James Kowalski

AI Benchmarks & Tools Analyst

James is a software engineer turned tech writer who spent six years building backend systems at a fintech startup in Chicago before pivoting to full-time analysis of AI tools and infrastructure. His engineering background means he doesn't just read the spec sheet - he runs the benchmarks, profiles the latency, and checks whether the marketing claims hold up under real workloads.

He studied Computer Science at the University of Illinois at Urbana-Champaign, where he first got hooked on natural language processing during a senior research project on sentiment analysis. He later completed a certificate in data journalism from Northwestern's Medill School.

At Awesome Agents, James owns the leaderboards and tool comparison coverage. He maintains the site's benchmark tracking methodology and is the person who actually runs the numbers before publishing any ranking. He is also an open-source advocate and contributes to several projects in the LLM inference space.

Based in Chicago, IL.

Articles by James Kowalski
Qwen3-Coder-Next

Qwen3-Coder-Next

Qwen3-Coder-Next is an 80B MoE coding model from Alibaba that activates just 3B parameters per forward pass, scoring over 70% on SWE-Bench Verified with agent scaffolding under Apache 2.0.

Gemini 3.5 Flash

Gemini 3.5 Flash

Google DeepMind's fastest frontier model, hitting 76.2% on Terminal-Bench 2.1 and 289 tok/s, now powering AI Mode in Search for over 1 billion monthly users.

Perplexity vs ChatGPT Search 2026

Perplexity vs ChatGPT Search 2026

Perplexity vs ChatGPT for search and research in 2026: real-time citations, Deep Research speed, pricing tiers, and which tool fits which workflow.