MiMo V2.5 vs Qwen3.8 Max

MiMo V2.5

Xiaomi · text, image, video, audio → text

MiMo-V2.5 is a native, fully multimodal large model designed for agent scenarios; it can see, hear, and read, and translate understanding into action. It has over 1 trillion total parameters (42B active parameters), employs an innovative hybrid-attention architecture, and supports an ultra-long 1M context length. Built on a powerful model base, we continuously scale compute across broader agent scenarios, further expanding the agent’s action space and achieving an important generalization from coding to claw.

Qwen3.8 Max

Qwen · text, image, video → text

Qwen3.8-Max is Alibaba Cloud Tongyi Qianwen's next-generation flagship large language model, featuring a mixture-of-experts (MoE) architecture with 2.4 trillion parameters. It achieves another breakthrough in encoding depth, enabling it to handle more complex engineering-grade projects and long-term autonomous development; collaborative agent capabilities are significantly enhanced, performing more confidently in multi-tool orchestration and end-to-end delivery; visual understanding is comprehensively improved, with more sensitive and accurate chart reasoning, document parsing, and multimodal perception. Continuing the 1-million-context window, reasoning modes, and a complete tool ecosystem, it continues to evolve at a higher level of intelligence.