Compare MiMo-V2.6-Pro vs. SWE-2 Flash in 2026

SWE-2 Flash

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Description

MiMo-V2.6-Pro is an open-source, natively omnimodal AI model from Xiaomi MiMo designed for coding, agentic workflows, visual creation, research, and computer-based tasks. It is the highest-capability model in the MiMo-V2.6 series and was trained using a large-scale reinforcement learning process focused on verifiable, complex tasks. The model can handle software engineering, automation, tool use, visual reasoning, and long-running agent workflows across multiple environments. Its multimodal capabilities extend beyond traditional coding into 3D scene generation, Blender modeling, embodied simulation, frontend development, presentation design, video creation, and music composition. MiMo-V2.6-Pro can take text, images, video, and other visual inputs and coordinate multi-agent workflows to produce and iteratively refine complex outputs. Research applications demonstrated by Xiaomi include materials discovery, literature analysis, computational simulation, hypothesis generation, and formalizing mathematical proofs in Lean. Xiaomi has released the model alongside its technical report, reinforcement learning environments, and RL code so researchers can study and reproduce the training approach. MiMo-V2.6-Pro is also available in an UltraSpeed configuration that provides substantially faster output for latency-sensitive workflows. Users can access the model through MiMo Desktop, AI Studio, MiMo Code, the MiMo API Platform, OpenRouter, and Hugging Face.

Description

SWE-2 Flash is a high-speed AI software engineering model developed by Cognition for automated coding, development workflows, and technical problem-solving. The model is based on Inkling-Small from Thinking Machines and uses a mixture-of-experts architecture containing 276 billion total parameters and 12 billion active parameters. Cognition applies large-scale mid-training and reinforcement learning to improve the model's programming accuracy, reasoning capabilities, and ability to complete complex software engineering tasks. SWE-2 Flash supports code generation, repository maintenance, automated code reviews, feature implementation, documentation updates, and agent-driven software development. Its optimized architecture delivers approximately 200 tokens per second, making it three times faster than SWE-2 while operating at one-fifth the inference cost. The model achieved a score of 24.0% on FrontierCode 2.0, 45.5% on FrontierCode 1.1 Main, and 89.2% on Terminal-Bench 2.1 in Cognition's published evaluations. Training improvements also target general reasoning, problem-solving, and cybersecurity tasks to expand the range of activities supported by autonomous coding agents. SWE-2 Flash is available in Devin Desktop and CLI, allowing developers to incorporate the model into interactive and automated software engineering workflows. Cognition is also developing a controlled model-weight access program for trusted industry partners and researchers interested in fine-tuning, infrastructure control, and deployment in sensitive environments.