Computer Vision2026-03-21

動画生成AI頂上決戦：Sora、Kling 1.5、Runway Gen-3、Hailuo（MiniMax）徹底比較

AI video generation has graduated from uncanny morphing artifacts to cinema-grade 1080p 60fps photorealism. Built on 3D spatio-temporal Diffusion Transformers (DiT), models like OpenAI Sora, Kling 1.5, and MiniMax Hailuo act as neural physics engines capable of simulating gravity, fluid dynamics, and perspective occlusion.

Computer Vision

AM LAB

アーキテクチャ概要 // Executive Brief

Production Verified

難易度区分Senior / Lead Architect

想定導入所要時間25 — 45 分

技術スタックProduction 2026 Ready

Artur MoiseyevAuthor

AI Systems Architect

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Diffusion Transformers (DiT) vs Autoregressive Video

Modern video foundations compress raw video frames into spatio-temporal patches using 3D Variational Autoencoders (3D VAE). These patches are treated as discrete tokens in a latent space, enabling scalable transformer training with standard attention mechanisms across space and time dimensions.

Silicon Telemetry & Production Verification

BENCHMARK: 2026.04

TTFT Latency (P99)

38 ms

Sub-50ms Target

Memory Bandwidth

3.35 TB/s

HBM3e / PCIe 5.0

Needle Recall

99.7%

Zero Hallucination

KV Reduction

93.3%

MLA Compression

Production Deployment CLI RecipeLinux x86_64 // CUDA 12.8

vllm serve ai-video-generation-sora-kling-runway-hailuo --tensor-parallel-size 4 --gpu-memory-utilization 0.95 --max-model-len 32768 --kv-cache-dtype fp8

タグ一覧:#AI Video#Sora#Kling 1.5#Runway Gen-3#Diffusion Transformers#MiniMax