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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Kimi K2 Thinking is a sophisticated open-source reasoning model created by Moonshot AI, specifically tailored for intricate, multi-step workflows where it effectively combines chain-of-thought reasoning with tool utilization across numerous sequential tasks. Employing a cutting-edge mixture-of-experts architecture, the model encompasses a staggering total of 1 trillion parameters, although only around 32 billion parameters are utilized during each inference, which enhances efficiency while retaining significant capability. It boasts a context window that can accommodate up to 256,000 tokens, allowing it to process exceptionally long inputs and reasoning sequences without sacrificing coherence. Additionally, it features native INT4 quantization, which significantly cuts down inference latency and memory consumption without compromising performance. Designed with agentic workflows in mind, Kimi K2 Thinking is capable of autonomously invoking external tools, orchestrating sequential logic steps—often involving around 200-300 tool calls in a single chain—and ensuring consistent reasoning throughout the process. Its robust architecture makes it an ideal solution for complex reasoning tasks that require both depth and efficiency.

Description

NVIDIA's Nemotron 3.5 Lightning is a state-of-the-art mixture-of-experts model boasting 30 billion parameters, of which 3 billion are actively utilized, specifically engineered for efficient, high-throughput performance in long-duration and continuously operating AI agents. This model is tailored for the execution components of agentic systems, adeptly managing frequent operations like tool invocations, output verification, routine commands, and delegating tasks to subagents, while larger reasoning models concentrate on strategic planning and orchestration. By employing a mixture-of-experts architecture, it activates only a select subset of parameters for each input token, marrying the expansive capacity of a larger model with significantly reduced computational demands. The training of this model is optimized for widely used agent harnesses and enhances inference speed through techniques such as speculative decoding, multi-token prediction, DFlash, and DSpark, making it versatile across various operational scenarios. Additionally, it is compatible with BF16 and NVFP4 checkpoints, providing flexibility in deployment from local systems like DGX Spark and GeForce RTX hardware to extensive data center infrastructures. In summary, its innovative design and scalability make it a powerful tool for advancing AI capabilities.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

OpenClaw
GPT-5.1
GPT-5.1 Pro
GPT-5.2 Instant
GPT-5.2 Pro
GPT-5.2 Thinking
GPT-5.3 Instant
GPT-5.4
GPT-5.4 Pro
GPT-5.4 nano
GPT-5.5
GPT-5.5 Pro
GPT-5.6 Luna
GPT-5.6 Terra
GPT-6
GPT‑5.4 Thinking
Hugging Face
NVIDIA NemoClaw
Nebius Token Factory
Oxlo.ai

Integrations

OpenClaw
GPT-5.1
GPT-5.1 Pro
GPT-5.2 Instant
GPT-5.2 Pro
GPT-5.2 Thinking
GPT-5.3 Instant
GPT-5.4
GPT-5.4 Pro
GPT-5.4 nano
GPT-5.5
GPT-5.5 Pro
GPT-5.6 Luna
GPT-5.6 Terra
GPT-6
GPT‑5.4 Thinking
Hugging Face
NVIDIA NemoClaw
Nebius Token Factory
Oxlo.ai

Pricing Details

Free
Open source
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Moonshot AI

Founded

2023

Country

United States

Website

moonshotai.github.io/Kimi-K2/thinking.html

Vendor Details

Company Name

NVIDIA

Founded

1993

Country

United States

Website

nvidia.com

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