DeepSeek V4 is out — Pro and Flash tiers, MIT license, 1M context, and pricing that undercuts the frontier by up to 11×. Here's how it stacks up against Qwen3.5, Kimi K2.5, MiniMax M2.7, GPT-5.4, and Claude Opus 4.6.

Kimi-Audio is an open-source audio foundation model capable of speech recognition, audio generation, and conversational AI tasks. While primarily designed for Linux environments, this guide provides detailed instructions for Windows users to leverage its capabilities through multiple methods. I. System Requirements 1. Hardware Specifications * GPU: NVIDIA GPU with ≥24GB VRAM

Kimi-Audio is a universal audio foundation model capable of audio understanding, generation, and processing. Kimi-Audio is an open-source AI model designed for audio-to-text (ASR) and audio-to-audio/text conversation tasks This guide adapts the workflow for macOSSystem Requirements and Compatibility Hardware Requirements * Apple Silicon (M1/M2/M3) or Intel-based Mac: * M-series

In the rapidly evolving field of artificial intelligence, particularly in vision-language models, two notable models have gained attention for their innovative approaches and capabilities: DeepSeek VL2 and Kimi Moonlight 3B. This article aims to provide a detailed comparison of these models, focusing on their architecture, capabilities, performance, and applications. Introduction

Kimi Moonlight is a cutting-edge 3B/16B-parameter Mixture-of-Expert (MoE) model developed by Kimi.ai, which has garnered significant attention for its performance in various benchmarks. This article will delve into the process of running Kimi Moonlight 3B on Windows, covering the necessary prerequisites, installation steps, and troubleshooting tips. What is

Kimi.ai's Moonlight model, a 3B/16B Mixture of Experts (MoE) model, has gained significant attention in the AI community for its impressive performance across various benchmarks. This article provides a step-by-step guide on running the Moonlight 3B model on macOS, covering prerequisites, setup, and troubleshooting tips. Prerequisites

Kimi.ai's Moonlight 3B/16B MoE model, trained with the advanced Muon optimizer, has gained attention in the AI community for its impressive performance and efficiency. This model is part of a broader trend in AI research, focusing on scalable models that can be deployed across different platforms.