GLM-5 and Kimi K2 Thinking are two of the strongest open-weight models from China's leading labs, and both top value charts. GLM-5, Z.ai's 744B MoE, is engineered for agentic coding and long-horizon tasks, leading the open-weights intelligence index at launch and excelling in coding harnesses like Claude Code and Cline.
Kimi K2 Thinking, Moonshot's trillion-parameter MoE, is the reasoning specialist — extensive chain-of-thought for hard math, coding and science, with a 256K context. GLM-5 tends to win on agentic engineering and tool-driven coding workflows; Kimi edges the deepest step-by-step reasoning problems. Both are open-weight, cheap and easy to integrate, so the choice hinges on agentic coding versus pure reasoning depth.
Which should you choose?
The verdict
GLM-5 leads on agentic engineering and coding workflows; Kimi K2 Thinking leads on deep step-by-step reasoning. Both are excellent open-weight value picks.
Watch the comparison
GLM-5 vs Kimi K2 Thinking — video reviews on YouTubeWatch hands-on tests and side-by-side demosFrequently asked questions
Which is better for coding agents?
GLM-5 is tuned for agentic engineering and shines in coding harnesses; Kimi K2 Thinking is stronger on the very hardest reasoning steps.
Are both open weight?
Yes — GLM-5 and Kimi K2 Thinking both ship open weights and are cheap to run or self-host.