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What is MiMo-V2.6-Flash?

MiMo-V2.6-Flash is an open-source, natively omnimodal AI model from Xiaomi MiMo built for users that need strong agentic and multimodal capabilities at a comparatively low operating cost. It is the efficiency-oriented model in the MiMo-V2.6 family, complementing the higher-capability MiMo-V2.6-Pro model. MiMo-V2.6-Flash supports software engineering, terminal-based workflows, tool use, automation, computer interaction, visual reasoning, and other multi-step agent tasks. Its multimodal abilities allow it to work with text, images, video, rendered environments, and other visual inputs when completing complex tasks. Xiaomi demonstrates the MiMo-V2.6 family generating frontend interfaces, presentation decks, 3D scenes, Blender assets, interactive worlds, and other visual outputs from natural-language or reference-based instructions. The models can also coordinate multiple agents, verify rendered results, and iteratively refine generated content based on visual feedback. In embodied simulation environments, MiMo-V2.6 can process multi-view camera feeds and continuously reason about actions such as object grasping, matching, and placement. MiMo-V2.6-Flash was trained with large-scale reinforcement learning across heterogeneous coding, general-agent, visual, and cybersecurity environments. Xiaomi reports that the Flash training run completed approximately 30 reinforcement learning steps across roughly 750,000 trajectories and significantly improved performance on held-out software engineering and automation evaluations. The company has released the MiMo-V2.6 series together with technical documentation, training environments, and reinforcement learning code so researchers can inspect and reproduce portions of the training approach. MiMo-V2.6-Flash is available through MiMo Desktop, AI Studio, MiMo Code, the Xiaomi MiMo API Platform, OpenRouter, and the project’s open-source distribution channels.

What is GPT-4.1 nano?

GPT-4.1 nano is a highly efficient, smaller-scale version of the GPT-4.1 model, built for high-speed, low-cost AI applications. It retains the core capabilities of the GPT-4.1 series, including support for a 1 million token context window, but with optimized performance for tasks like classification, search, and autocompletion. Designed to be both affordable and fast, GPT-4.1 nano is perfect for developers and businesses looking for a quick, reliable AI solution that minimizes latency and operational costs.

Media

Media

Integrations Supported

BLACKBOX AI
Canopy Wave
Cline
ClinePass
Hermes Agent
Hugging Face
Kilo Code
OpenClaw
Roo Code
Shiori
Vercel AI Gateway
Xiaomi MiMo Studio

Integrations Supported

BLACKBOX AI
Cheaper Inference
GPT-4.1
GPT-4.1 mini
GitHub Copilot
HTML
Microsoft Foundry
Microsoft Foundry Models
Snowflake

API Availability

Has API

API Availability

Has API

Pricing Information

Free
$0.14 per 1 million tokens input
$0.28 per 1 million tokens output
Free Version

Pricing Information

$0.10 per 1M tokens (input)
$0.10 per 1 million tokens (input)
$0.025 per 1 million tokens (cached input)
$0.40 per 1 million tokens (output)

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Xiaomi Technology

Date Founded

2010

Company Location

China

Company Website

mimo.xiaomi.com

Company Facts

Organization Name

OpenAI

Date Founded

2015

Company Location

United States

Company Website

openai.com/index/gpt-4-1/

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

AI Reasoning Models

Not specified

AI Vision Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

Multimodal Models

Not specified

Open-Weight AI Models

Not specified

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

AI Reasoning Models

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

Multimodal Models

Not specified

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