MoonshotAI's large MoE model — 1T total parameters, 32B active.
Open-source 1.6T-parameter MoE with 49B active, built for advanced reasoning and long-horizon agents.
No shared agent demos for these models yet.
No captured outputs for these models yet.
Based on the Capability Index, DeepSeek V4 Pro scores higher (81.6 vs 78.2). However, "better" depends on your use case — pricing, speed, context window, and specific capability needs all matter.
DeepSeek V4 Pro has a lower blended cost. Kimi K2: $0.57 input / $2.30 output. DeepSeek V4 Pro: $0.43 input / $0.87 output.
DeepSeek V4 Pro has a larger context window: Kimi K2 supports 131K tokens vs DeepSeek V4 Pro at 1M tokens.
Key differences: only DeepSeek V4 Pro 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 DeepSeek V4 Pro for free on idapt.app to see which performs better for your specific needs.