Average Ratings 1 Rating

Total
ease
features
design

Average Ratings 1 Rating

Total
ease
design

Description

Laguna S 2.1 is an advanced open weight coding model that emphasizes long-term project completion and efficient reasoning capabilities. Featuring a 118-billion-parameter Mixture-of-Experts architecture, it activates 8 billion parameters for each token and accommodates a context window of up to one million tokens in both thinking and non-thinking modes. The model’s streamlined active size allows it to perform intricate tasks on local machines while still competing favorably against significantly larger models across various benchmarks, including terminal usage, software engineering, codebase question answering, and tool utilization. Designed for resilience, Laguna S 2.1 excels in tackling challenging assignments with enhanced persistence, meticulous verification, and a readiness to backtrack rather than prematurely claim success. In practical applications, it has successfully created and validated a browser rendering engine from scratch, optimized an agent harness for improved execution speed and reduced memory usage, and conducted extensive mathematical research using the available tools within its environment, demonstrating its versatility and effectiveness. This combination of features positions Laguna S 2.1 as a powerful tool for developers seeking innovative solutions.

Description

MiMo-V2.6-Flash is Xiaomi MiMo’s efficiency-focused open-source omnimodal model for coding, automation, visual work, and agentic applications. It is designed to provide a balance between model capability, inference cost, and practical performance across a broad range of workloads. The model can perform software engineering tasks, use tools, execute multi-step workflows, and interact with computer environments. Its multimodal capabilities support applications such as frontend development, presentation design, 3D content creation, game development, and visual reasoning. MiMo-V2.6 can also use multi-view visual inputs in embodied simulation environments to reason about scenes and guide actions through feedback loops. Xiaomi trained the Flash model using reinforcement learning over roughly 750,000 trajectories spanning coding, general agents, visual tasks, and cybersecurity environments. During that training process, Xiaomi reports substantial gains in long-horizon software engineering and general workflow performance compared with the model’s earlier checkpoints. The company has open-sourced the broader MiMo-V2.6 release along with its technical report, reinforcement learning environments, and RL code to support research and reproducibility. MiMo-V2.6-Flash can be accessed through MiMo Desktop, AI Studio, MiMo Code, the MiMo API Platform, OpenRouter, and Xiaomi MiMo’s open-source distribution channels.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Cline Yes 
Hermes Agent Yes 
Hugging Face Yes 
Kilo Code Yes 
OpenClaw Yes 
OpenCode Yes 
OpenRouter Yes 
Roo Code Yes 
Canopy Wave No 
Claude Code Yes 
ClinePass No 
Nous Portal Yes 
Ollama Yes 
Shiori No 
Vercel AI Gateway No 
Visual Studio Code Yes 
Xiaomi MiMo No 
Xiaomi MiMo Desktop No 
Xiaomi MiMo Studio No 
Zed Yes 

Integrations

Cline Yes 
Hermes Agent Yes 
Hugging Face Yes 
Kilo Code Yes 
OpenClaw Yes 
OpenCode Yes 
OpenRouter Yes 
Roo Code Yes 
Canopy Wave Yes 
Claude Code No 
ClinePass Yes 
Nous Portal No 
Ollama No 
Shiori Yes 
Vercel AI Gateway Yes 
Visual Studio Code No 
Xiaomi MiMo Yes 
Xiaomi MiMo Desktop Yes 
Xiaomi MiMo Studio Yes 
Zed No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

Free
$0.14 per 1 million tokens input
$0.28 per 1 million tokens output
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Poolside

Founded

2023

Country

United States

Website

poolside.ai/blog/introducing-laguna-s-2-1

Vendor Details

Company Name

Xiaomi Technology

Founded

2010

Country

China

Website

mimo.xiaomi.com

Product Features

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Alternatives

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