MiMo-V2.6-Pro vs. Claude Haiku 5.5

MiMo-V2.6-Pro is Xiaomi MiMo’s flagship open-source omnimodal model for software engineering, agentic automation, multimodal reasoning, visual design, research, and creative production. The model was developed through large-scale reinforcement learning on heterogeneous tasks spanning coding, general agents, visual workflows, and cybersecurity. Xiaomi trained MiMo-V2.6-Pro across roughly 750,000 trajectories using large asynchronous batches, long-context training, multi-task environments, and expanded grader compute. The resulting model is designed to plan, execute, verify, and refine complex work across multiple tools and interaction environments. In software development, MiMo-V2.6-Pro supports long-horizon coding, terminal work, automation, debugging, and other agent-driven engineering tasks. Its multimodal capabilities allow it to generate interactive 3D worlds, create Blender assets from text or reference images, and control simulated robotic systems using continuous visual feedback. The model can also build frontend interfaces, design slide decks, work with Figma and media-generation tools, and automate portions of video production from concept through editing and narration. Creative capabilities extend to music composition, including generating arrangements, musical scores, and MIDI output. For research, MiMo-V2.6-Pro has been demonstrated performing literature searches, generating scientific hypotheses, running computational tools, screening materials, and assisting with formal mathematical proofs. Xiaomi has open-sourced the model family together with its technical report, reinforcement learning environments, and training code to support reproducibility and further research. MiMo-V2.6-Pro is available through Xiaomi MiMo’s desktop and developer products, OpenRouter, Hugging Face, and an API, with an UltraSpeed version offered for workflows that require much faster generation.

Claude Haiku 5.5 is an Anthropic AI model built for high-volume and latency-sensitive AI workloads that require a balance of speed, cost, context capacity, and reasoning. Its primary use cases include classification, routing, information extraction, and subagent tasks within larger AI systems. Claude Haiku 5.5 introduces adaptive thinking, which allows the model to decide when reasoning is needed and how much thinking to apply before producing a response. Adaptive thinking is enabled by default, while the effort parameter gives developers a way to trade response quality against latency and cost. Developers can disable thinking at high effort or below, but Anthropic recommends using effort as the primary mechanism for controlling the model's reasoning behavior. The model provides a 1 million token context window, representing a substantial increase from the 200,000-token context window available with Claude Haiku 4.5. It can generate as many as 128,000 output tokens compared with the previous model's 64,000-token maximum, although thinking tokens are included within the configured output allowance. Browser use is available through the Claude API and Google Cloud, enabling developers to incorporate the model into workflows that require interaction with browser-based environments. Claude Haiku 5.5 uses the newer tokenizer found in Claude 4.7 and later models, resulting in approximately 30% more tokens for the same text compared with Claude Haiku 4.5, depending on the content. The model also changes several API behaviors, including replacing manual extended thinking with adaptive thinking, rejecting non-default sampling parameters and assistant-message prefills, and requiring updated computer-use tooling for supported environments.