Compare MiMo-V2.6-Pro-UltraSpeed vs. Qwen3.8-2.4T-A95B in 2026

Qwen3.8-2.4T-A95B

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Description

MiMo-V2.6-Pro-UltraSpeed is Xiaomi MiMo’s accelerated serving option for MiMo-V2.6-Pro, built for applications that require very high output speed without changing the underlying model quality. Xiaomi states that UltraSpeed can generate output at up to 20 times the speed of the standard MiMo-V2.6-Pro configuration. The model retains MiMo-V2.6-Pro’s natively omnimodal capabilities across coding, agentic workflows, visual reasoning, computer use, and research. Developers can use it for long-horizon software engineering, automation, debugging, tool-driven tasks, and other workloads that benefit from rapid model responses. Its multimodal abilities also support frontend generation, presentation creation, 3D modeling, interactive environments, and visual feedback loops. The broader MiMo-V2.6 architecture combines coding capabilities with 3D spatial reasoning, multimodal perception, and computer-use agent functionality. Xiaomi positions UltraSpeed for real-time interaction and other workflows where response latency is especially important. The accelerated model is offered through MiMo Desktop and can also be called through the Xiaomi MiMo API Platform. MiMo-V2.6-Pro-UltraSpeed is intended for developers and organizations that prioritize maximum generation speed while retaining the capabilities of Xiaomi’s higher-end MiMo-V2.6-Pro model.

Description

Qwen3.8-2.4T-A95B stands out as the most extensive open model within the Qwen3.8 series, offering advanced Qwen-Max-class features in a publicly accessible format. Constructed upon the solid framework of Qwen3.5, this model significantly enhances performance in areas such as coding, professional tasks, research, and complex, prolonged agentic activities, emphasizing the reliability of executing intricate, multi-step workflows to completion. Utilizing a cutting-edge mixture-of-experts architecture, it boasts an impressive total of 2.4 trillion parameters, with 95 billion of those being activated, featuring 512 experts and engaging 10 routed along with one shared expert simultaneously. The model accommodates a native context length of 262,144 tokens, which can be extended to around 1.01 million tokens, thereby providing substantial flexibility for various applications. Furthermore, improvements in agent execution, such as enhanced autonomous planning and better responsiveness to environmental feedback, contribute to its efficiency, while its broader compatibility with widely used agent frameworks and development tools facilitates seamless integration into existing systems, making it a versatile choice for developers and researchers alike.