Inception's latest diffusion LLM and the fastest reasoning model available, producing and refining tokens in parallel instead of one at a time.
MoonshotAI's coding-focused Kimi model for end-to-end software engineering.
No shared demos for these models yet.
No captured outputs for these models yet.
Both Mercury 2.5 and Kimi K2.7 Code 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.
Mercury 2.5 has a lower blended cost. Mercury 2.5: $0.04 input / $0.15 output. Kimi K2.7 Code: $0.82 input / $3.75 output.
Kimi K2.7 Code has a larger context window: Mercury 2.5 supports 260K tokens vs Kimi K2.7 Code at 262K tokens.
Kimi K2.7 Code supports vision/image input, but Mercury 2.5 does not.
Key differences: Mercury 2.5 is significantly cheaper; only Kimi K2.7 Code supports vision input. 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 Mercury 2.5 and Kimi K2.7 Code for free on idapt.app to see which performs better for your specific needs.