MoonshotAI's large MoE model — 1T total parameters, 32B active.
Google's fourth-generation open dense model with native multimodal understanding.
No shared agent demos for these models yet.
No captured outputs for these models yet.
Both Kimi K2 and Gemma 4 31B are capable AI models. The best choice depends on your specific use case: consider pricing, context window, speed, and which capabilities (vision, reasoning, audio) you need.
Gemma 4 31B has a lower blended cost. Kimi K2: $0.57 input / $2.30 output. Gemma 4 31B: $0.12 input / $0.37 output.
Gemma 4 31B has a larger context window: Kimi K2 supports 131K tokens vs Gemma 4 31B at 262K tokens.
Gemma 4 31B supports vision/image input, but Kimi K2 does not.
Key differences: Gemma 4 31B is significantly cheaper; only Gemma 4 31B supports vision input; only Gemma 4 31B 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 Kimi K2 and Gemma 4 31B for free on idapt.app to see which performs better for your specific needs.