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Description

The Ling 2.6 Flash represents the newest and most economical addition to the Ling series, utilizing a Mixture of Experts architecture that encompasses a total of 104 billion parameters, with 7.4 billion of those being actively engaged. This model is crafted to strike an ideal balance between inference speed and computational expense, making it an excellent fit for diverse scenarios where reasoning prowess, high throughput, and effective deployment are essential. By employing its MoE structure, Ling ensures that each token activates only the most pertinent expert subnetworks, significantly reducing the actual computational load while preserving the expansive capacity of the model. Offering a native context window of 256K, Ling 2.6 Flash is capable of handling around 200,000 characters of lengthy input, adeptly retrieving critical long-range information regardless of its position in the context. Furthermore, its overall benchmark performance rivals or surpasses that of 40 billion parameter Dense models, highlighting its competitive edge in the field of AI. This blend of efficiency and performance makes Ling 2.6 Flash a noteworthy option for developers seeking advanced capabilities without excessive resource demands.

Description

MiniMax M3 is a frontier open-weight AI model built for coding, agentic work, multimodal understanding, and ultra-long-context tasks. The model supports up to a 1 million token context window, allowing it to work across large codebases, long documents, logs, project histories, and complex task environments. MiniMax M3 introduces MiniMax Sparse Attention, a sparse attention architecture designed to make long-context processing more efficient. The model is natively multimodal, with training that supports deeper semantic fusion across text, image, and video inputs. It is designed to support software engineering tasks, repository analysis, terminal-style work, browser-style retrieval, tool use, and autonomous workflows. MiniMax M3 has a mixture-of-experts architecture with hundreds of billions of total parameters and a smaller activated parameter count for more efficient inference. Developers can use it for AI coding assistants, workflow automation, research agents, document analysis, visual reasoning, and enterprise AI systems. Its long-context capability makes it especially useful when tasks require many files, references, instructions, or interaction histories to stay available at once. MiniMax M3 helps teams build more capable AI agents that can understand larger problems, work across multiple modalities, and execute complex tasks with stronger context awareness.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Claude Code Yes 
Hermes Agent Yes 
Kilo Code Yes 
OpenClaw Yes 
APIFree No 
Alibaba AI Coding Plan No 
BLACKBOX AI No 
ClinePass No 
Factory Droid No 
Fireworks AI No 
MiniMax Code No 
MiniMax Mavis No 
Ollama No 
OpenCode Go No 
OpenCode Zen No 
OpenRouter Yes 
OpenTag No 
Roo Code No 
Vision Agents No 
ZenMux Yes 

Integrations

Claude Code Yes 
Hermes Agent Yes 
Kilo Code Yes 
OpenClaw Yes 
APIFree Yes 
Alibaba AI Coding Plan Yes 
BLACKBOX AI Yes 
ClinePass Yes 
Factory Droid Yes 
Fireworks AI Yes 
MiniMax Code Yes 
MiniMax Mavis Yes 
Ollama Yes 
OpenCode Go Yes 
OpenCode Zen Yes 
OpenRouter No 
OpenTag Yes 
Roo Code Yes 
Vision Agents Yes 
ZenMux No 

Pricing Details

$0.00037 per 1M tokens
Free Trial No 
Free Version No 

Pricing Details

$0.30 per million input tokens
$0.30 per million input tokens and $1.20 per million output tokens
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 Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
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 No 
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

Ant Group

Founded

2014

Country

China

Website

developer.ant-ling.com/en/docs/models/ling/

Vendor Details

Company Name

MiniMax

Founded

2021

Country

Singapore

Website

www.minimax.io

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