Google's high-speed thinking model for agentic workflows, chat, and coding.
MoonshotAI's large MoE model — 1T total parameters, 32B active.
No shared demos for these models yet.
No captured outputs for these models yet.
Based on the Capability Index, Gemini 3.5 Flash scores higher (86.2 vs 78.2). However, "better" depends on your use case — pricing, speed, context window, and specific capability needs all matter.
Kimi K2 has a lower blended cost. Gemini 3.5 Flash: $1.50 input / $9.00 output. Kimi K2: $0.57 input / $2.30 output.
Gemini 3.5 Flash has a larger context window: Gemini 3.5 Flash supports 1M tokens vs Kimi K2 at 131K tokens.
Gemini 3.5 Flash supports vision/image input, but Kimi K2 does not.
Key differences: Gemini 3.5 Flash has a notably higher capability index (8.0 point gap); Kimi K2 is significantly cheaper; only Gemini 3.5 Flash supports vision input; only Gemini 3.5 Flash offers extended reasoning mode. Compare full specs on this page.
If cost is your priority, choose the cheaper option. If you need the highest intelligence for complex tasks, pick the higher-scoring model. For long documents or codebases, choose the larger context window. You can try both Gemini 3.5 Flash and Kimi K2 for free on idapt.app to see which performs better for your specific needs.