Kimi K2.7-Code
Moonshot AI's Kimi K2.7-Code is a 1T-parameter open-weight MoE coding model with mandatory thinking mode, 256K context, and 30% fewer reasoning tokens than K2.6.
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
MAI-Thinking-1
Microsoft's first in-house reasoning model, a 35B-active sparse MoE with 256K context, 97% on AIME 2025, and no distillation from third-party labs.
Best AI Models for RAG - June 2026
Gemini 2.5 Flash still leads LIT-RAGBench English RAG accuracy at 87.0%, but the full benchmark data reveals two overlooked entries: GPT-4.1-mini at 84.1% and o4-mini at 83.9%.
Best AI Coding IDEs 2026: Cursor, Windsurf, Kiro, Zed, Copilot
A benchmark-driven comparison of the five leading AI coding IDEs in 2026, covering pricing, agent capabilities, and who each one is actually built for.
DiffusionGemma 26B
DiffusionGemma 26B is Google DeepMind's open-weight discrete diffusion language model that generates 256 tokens in parallel, reaching 1,100+ tokens/sec on H100 - roughly 4x faster than autoregressive models of the same size.
Claude Fable 5
Claude Fable 5 is Anthropic's first publicly available Mythos-class model, with safety classifiers that fall back to Claude Opus 4.8 for high-risk requests across cybersecurity, biology, and chemistry.
MAI-Code-1-Flash
Microsoft's first in-house coding model, a 137B sparse MoE built natively for GitHub Copilot, beating Claude Haiku 4.5 on SWE-Bench Pro by 16 points.
Ministral 3 8B
Mistral AI's mid-tier open-weight edge model - 8B parameters, 256K context, Apache 2.0 license, built for agentic pipelines and cost-sensitive production workloads.
Devstral 2
Mistral's open-weight coding agent model - 123B parameters, 256K context window, 72.2% on SWE-bench Verified, priced at $0.40/M input tokens.
Grok Build 0.1
Grok Build 0.1 is xAI's first model built specifically for agentic coding workflows, with a 256K context window, native MCP support, and always-on reasoning at $1/M input tokens.
Ministral 3 14B
Mistral AI's largest Ministral 3 model - 14B parameters, 256K context, Apache 2.0 license, multimodal, built for local deployment and agentic workflows.
NVIDIA Nemotron 3 Ultra 550B-A55B
NVIDIA's 550B open-weight MoE model with 55B active parameters, hybrid Mamba-Transformer architecture, and 1M token context - the top-scoring US open model on the Artificial Analysis Intelligence Index.
