Xiaomi's native omnimodal model delivering Pro-level agentic performance at roughly half the inference cost.
Google's fourth-generation open dense model with native multimodal understanding.
No shared demos for these models yet.
No captured outputs for these models yet.
Both MiMo V2.5 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.
MiMo V2.5 has a lower blended cost. MiMo V2.5: $0.14 input / $0.28 output. Gemma 4 31B: $0.20 input / $0.40 output.
MiMo V2.5 has a larger context window: MiMo V2.5 supports 1M tokens vs Gemma 4 31B at 262K tokens.
Yes, both MiMo V2.5 and Gemma 4 31B support vision/image input.
MiMo V2.5 and Gemma 4 31B have similar overall capabilities. The main differences lie in pricing, context window size, and provider-specific strengths. Use this comparison page to review all metrics side by side.
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 MiMo V2.5 and Gemma 4 31B for free on idapt.app to see which performs better for your specific needs.