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What is Ling 2.6?
Ling 2.6 signifies a series of large language models that have been independently developed and made open-source by Ant Group, leveraging a Mixture of Experts (MoE) architecture to optimize inference efficiency, manage long context modeling, improve training methodologies, and facilitate collaborative reasoning among AI agents. Through the implementation of this MoE architecture, Ling adeptly channels each token to interact solely with the most relevant expert subnetworks, which markedly decreases computational demands while maintaining the model's extensive functional capabilities. Notably, this series achieves significant advancements in long-sequence modeling, as demonstrated by Ling-2.6-1T, which supports a native context window of up to 1 million tokens and provides a 256K context window via its official API; further, Ling-2.6-flash is designed with a native 256K context window, allowing it to process approximately 200,000 characters in large inputs. These models are designed with great precision to ensure the reliable retrieval of information over long distances without any noticeable degradation in quality, regardless of the position of the data within the context. This cutting-edge methodology in long-context processing establishes a new standard for both efficiency and reliability in the performance of language models. The implications of such advancements could revolutionize how AI systems interact with extensive data sets, enabling more sophisticated applications in various fields.
What is Kimi K3?
Kimi K3 is Moonshot AI’s most advanced model, designed for high-end reasoning, software engineering, multimodal understanding, knowledge work, and agentic AI applications. The model has 2.8 trillion parameters and is built on Kimi Delta Attention, a hybrid linear attention mechanism created for long-context performance. It also uses Attention Residuals and supports a native context window of up to 1 million tokens. This makes Kimi K3 suitable for tasks involving large codebases, long research materials, enterprise documentation, multi-file analysis, legal documents, technical manuals, and complex workflows. Kimi K3 always has thinking mode enabled, with reasoning effort configured through the reasoning_effort field and maximum effort currently supported as the default. Developers can use the model through an OpenAI-compatible API, making it easier to integrate with existing SDKs, clients, and application infrastructure. The model supports streaming responses with separate reasoning and final-answer deltas, allowing applications to display reasoning progress and final content differently. Kimi K3 also supports strict structured output with JSON Schema, partial mode for continuing from a prefix, custom tool calling, required tool use, and dynamic tool loading through system messages. Its vision capabilities support image and video inputs through base64 or uploaded files, enabling analysis of visual content alongside text. Automatic context caching helps workflows that reuse long prefixes, such as large knowledge bases or persistent system context, without requiring developers to manage cache IDs manually. By combining frontier-scale parameters, long-context processing, visual input, structured outputs, tool orchestration, and developer-friendly API compatibility, Kimi K3 gives teams a strong foundation for advanced AI agents, coding assistants, research systems, enterprise automation, and multimodal applications.
Integrations Supported
Claude Code
Hermes Agent
OpenClaw
.NET
Brokk
C
CSS
Cheaper Inference
Factory Droid
HTML
Integrations Supported
Claude Code
Hermes Agent
OpenClaw
.NET
Brokk
C
CSS
Cheaper Inference
Factory Droid
HTML
API Availability
Has API
API Availability
Has API
Pricing Information
$0.0028 per 1M tokens
Free Version
Free Trial Offered?
Pricing Information
$3 per 1M tokens (input)
Kimi K3 is priced per 1 million tokens:
Cached input: $0.30
Uncached input: $3.00
Output: $15.00
Context window: 1,048,576 tokens
Cached inputs cost 90% less than uncached inputs, while generated output is the most expensive token category. Prices exclude applicable taxes, which are calculated based on the customer’s jurisdiction.
Cached input: $0.30
Uncached input: $3.00
Output: $15.00
Context window: 1,048,576 tokens
Cached inputs cost 90% less than uncached inputs, while generated output is the most expensive token category. Prices exclude applicable taxes, which are calculated based on the customer’s jurisdiction.
Free Version
Free Trial Offered?
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Ant Group
Date Founded
2014
Company Location
China
Company Website
developer.ant-ling.com/en/docs/models/ling/
Company Facts
Organization Name
Moonshot AI
Date Founded
2023
Company Location
China
Company Website
kimi.ai