OpenAI o3-pro
OpenAI's maximum-compute reasoning model targets the hardest problems where o3 falls short, at $20/$80 per million tokens.
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
OpenAI o3
OpenAI's most advanced reasoning model, built for math, science, coding, and visual tasks, with 200K context and adaptive chain-of-thought at $2/$8 per million tokens.
OpenAI o4-mini
OpenAI o4-mini is a fast, cost-efficient reasoning model in the o-series, delivering near-o3 performance on math and coding benchmarks at roughly 10x lower cost.
GPT-4.1
OpenAI's coding-optimized API model with a 1M token context window, 54.6% SWE-bench Verified score, and $2/$8 per million token pricing.
Claude 3.7 Sonnet
Anthropic's first hybrid reasoning model with togglable extended thinking, a 200K context window, and state-of-the-art SWE-bench performance at $3/$15 per million tokens.
