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What is Kimi K2 Thinking?

Kimi K2 Thinking is an advanced open-source reasoning model developed by Moonshot AI, specifically designed for complex, multi-step workflows where it adeptly merges chain-of-thought reasoning with the use of tools across various sequential tasks. It utilizes a state-of-the-art mixture-of-experts architecture, encompassing an impressive total of 1 trillion parameters, though only approximately 32 billion parameters are engaged during each inference, which boosts efficiency while retaining substantial capability. The model supports a context window of up to 256,000 tokens, enabling it to handle extraordinarily lengthy inputs and reasoning sequences without losing coherence. Furthermore, it incorporates native INT4 quantization, which dramatically reduces inference latency and memory usage while maintaining high performance. Tailored for agentic workflows, Kimi K2 Thinking can autonomously trigger external tools, managing sequential logic steps that typically involve around 200-300 tool calls in a single chain while ensuring consistent reasoning throughout the entire process. Its strong architecture positions it as an optimal solution for intricate reasoning challenges that demand both depth and efficiency, making it a valuable asset in various applications. Overall, Kimi K2 Thinking stands out for its ability to integrate complex reasoning and tool use seamlessly.

What is DeepSeek-V2?

DeepSeek-V2 represents an advanced Mixture-of-Experts (MoE) language model created by DeepSeek-AI, recognized for its economical training and superior inference efficiency. This model features a staggering 236 billion parameters, engaging only 21 billion for each token, and can manage a context length stretching up to 128K tokens. It employs sophisticated architectures like Multi-head Latent Attention (MLA) to enhance inference by reducing the Key-Value (KV) cache and utilizes DeepSeekMoE for cost-effective training through sparse computations. When compared to its earlier version, DeepSeek 67B, this model exhibits substantial advancements, boasting a 42.5% decrease in training costs, a 93.3% reduction in KV cache size, and a remarkable 5.76-fold increase in generation speed. With training based on an extensive dataset of 8.1 trillion tokens, DeepSeek-V2 showcases outstanding proficiency in language understanding, programming, and reasoning tasks, thereby establishing itself as a premier open-source model in the current landscape. Its groundbreaking methodology not only enhances performance but also sets unprecedented standards in the realm of artificial intelligence, inspiring future innovations in the field.

Media

Media

Integrations Supported

GPT-5.1
GPT-5.1 Thinking
GPT-5.2
GPT-5.3 Instant
GPT-5.4
GPT-5.4 Pro
GPT-5.4 mini
GPT-5.4 nano
GPT-5.5
GPT-5.5 Pro
GPT-5.6 Sol
GPT-6.1 Sol
GPT‑5.4 Thinking
Hugging Face
Nebius Token Factory
OpenAI Bel
OpenClaw
Oxlo.ai
Shiori

Integrations Supported

SiliconFlow

API Availability

API Availability

Has API

Pricing Information

Free
Open source
Free Version

Pricing Information

Free
Open source
Free Version

Supported Platforms

SaaS
Windows
Mac
On-Prem
Linux

Supported Platforms

Windows
Mac
On-Prem
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Not specified

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Moonshot AI

Date Founded

2023

Company Location

United States

Company Website

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

Company Facts

Organization Name

DeepSeek

Date Founded

2023

Company Location

China

Company Website

deepseek.com

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

Open-Weight AI Models

Not specified

Categories and Features

AI Coding Models

Not specified

AI Models

Not specified

Large Language Models

Not specified

Open-Weight AI Models

Not specified

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