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
Best AI Models for Video Generation - June 2026

Best AI Models for Video Generation - June 2026

HappyHorse-1.0 from Alibaba-ATH leads the Artificial Analysis blind-vote rankings at Elo 1,290, but Seedance 2.0 is now globally available via fal.ai and still tops the with-audio leaderboard at 1,218.

GPT-5.5-Cyber

GPT-5.5-Cyber

OpenAI's GPT-5.5-Cyber is a cybersecurity-specialized fine-tune of GPT-5.5, restricted to vetted defenders through the Daybreak Cyber Partner Program and rated 85.6% on the CyberGym benchmark.

Sakana Fugu

Sakana Fugu

Sakana AI's orchestrator model that dynamically coordinates Claude Opus 4.8, GPT-5.5, and Gemini 3.1 Pro to beat each of them individually on SWE-Bench Pro, GPQA-Diamond, and eight other benchmarks.

VibeThinker-3B

VibeThinker-3B

WeiboAI's 3B dense reasoning model fine-tuned from Qwen2.5-Coder-3B, posting AIME 2026 scores that match DeepSeek V3.2 (671B) using the Spectrum-to-Signal training pipeline.

Fara-1.5

Fara-1.5

Microsoft Research's family of open-weight browser computer use agents (4B, 9B, 27B) that beat OpenAI Operator and Gemini 2.5 Computer Use on Online-Mind2Web.

ERNIE 5.1

ERNIE 5.1

Baidu's ERNIE 5.1 is a text-focused MoE model that claims the top Chinese model slot on LMArena with 800B parameters built at 6% of comparable training costs.

MAI-Transcribe-1.5

MAI-Transcribe-1.5

Microsoft's second-generation speech-to-text model with 2.4% WER, 43-language support, keyword biasing, and 5x faster long-audio processing than comparable accuracy models.

Voxtral TTS

Voxtral TTS

Mistral's first open-weight text-to-speech model: 4B parameters, 70ms latency, voice cloning from 3 seconds of audio, and a 68.4% win rate over ElevenLabs Flash v2.5 in blind tests.

GPT-5.1

GPT-5.1

GPT-5.1 is OpenAI's November 2025 coding and agentic flagship with 400K context, configurable reasoning effort, and 76.3% on SWE-bench Verified.