{"@context":"https://schema.org","@type":"NewsArticle","generatedAt":"2026-08-11T11:14:02.523Z","headline":"用 ComfyUI API 实现 MiniMax-H3 多模态视频与音频生成流水线","description":"本教程演示如何以 ComfyUI 为无头推理后端，构建端到端的 MiniMax-H3 视频生成工作流。通过 Python 直接构建执行图，支持文生视频、首尾帧条件生成和参考图像条件生成，并自动根据 GPU 显存选择 quality、balanced、squeeze 三种权重配置。流水线涵盖模型自动下载、节点模式校验、音视频联合解码与进度监控，无需图形界面即可复现实验。 🔗 阅读原文 via AIHOT · https://aihot.virxact.com/items/cmso8nqa70eq4rofw24w1wlwt","url":"https://www.aioga.com/news/cmso8nqa70eq4rofw24w1wlwt/","mainEntityOfPage":"https://www.aioga.com/news/cmso8nqa70eq4rofw24w1wlwt/","datePublished":"2026-08-11T05:44:38.000Z","dateModified":"2026-08-11T05:44:38.000Z","inLanguage":"zh-CN","publisher":{"@type":"NewsMediaOrganization","name":"Aioga","url":"https://www.aioga.com"},"citation":["https://www.marktechpost.com/2026/08/10/implementing-a-minimax-h3-multimodal-video-and-audio-generation-pipeline-with-comfyui-apis","https://aihot.virxact.com/items/cmso8nqa70eq4rofw24w1wlwt"],"canonicalUrl":"https://www.aioga.com/news/cmso8nqa70eq4rofw24w1wlwt/","directAnswer":{"@type":"Answer","text":"Aioga 编辑摘要：本教程演示如何以 ComfyUI 为无头推理后端，构建端到端的 MiniMax-H3 视频生成工作流。 Aioga 将其归入「行业动态」方向，重点关注它对真实使用和行业竞争的影响。","url":"https://www.aioga.com/news/cmso8nqa70eq4rofw24w1wlwt/","dateCreated":"2026-08-11T05:44:38.000Z","author":{"@type":"Organization","@id":"https://www.aioga.com/authors/aioga-editorial/#editorial-team","name":"Aioga Editorial Team","url":"https://www.aioga.com/authors/aioga-editorial/"}},"evidence":[{"@type":"CreativeWork","name":"marktechpost.com source article","url":"https://www.marktechpost.com/2026/08/10/implementing-a-minimax-h3-multimodal-video-and-audio-generation-pipeline-with-comfyui-apis","datePublished":"2026-08-11T05:44:38.000Z","provider":{"@type":"Organization","name":"marktechpost.com","url":"https://www.marktechpost.com/2026/08/10/implementing-a-minimax-h3-multimodal-video-and-audio-generation-pipeline-with-comfyui-apis"}},{"@type":"CreativeWork","name":"AIHot archive record","url":"https://aihot.virxact.com/items/cmso8nqa70eq4rofw24w1wlwt","datePublished":"2026-08-11T05:44:38.000Z","provider":{"@type":"Organization","name":"AIHot","url":"https://aihot.virxact.com/items/cmso8nqa70eq4rofw24w1wlwt"}}],"aggregationSource":"MarkTechPost（RSS）","originalPublisher":{"name":"marktechpost.com","url":"https://www.marktechpost.com/2026/08/10/implementing-a-minimax-h3-multimodal-video-and-audio-generation-pipeline-with-comfyui-apis"},"geoDeepAnswer":null,"article":{"id":"cmso8nqa70eq4rofw24w1wlwt","slug":"cmso8nqa70eq4rofw24w1wlwt","url":"https://www.aioga.com/news/cmso8nqa70eq4rofw24w1wlwt/","title":"用 ComfyUI API 实现 MiniMax-H3 多模态视频与音频生成流水线","title_en":"","summary":"本教程演示如何以 ComfyUI 为无头推理后端，构建端到端的 MiniMax-H3 视频生成工作流。通过 Python 直接构建执行图，支持文生视频、首尾帧条件生成和参考图像条件生成，并自动根据 GPU 显存选择 quality、balanced、squeeze 三种权重配置。流水线涵盖模型自动下载、节点模式校验、音视频联合解码与进度监控，无需图形界面即可复现实验。 🔗 阅读原文 via AIHOT · https://aihot.virxact.com/items/cmso8nqa70eq4rofw24w1wlwt","source":"MarkTechPost（RSS）","sourceUrl":"https://www.marktechpost.com/2026/08/10/implementing-a-minimax-h3-multimodal-video-and-audio-generation-pipeline-with-comfyui-apis","aiHotUrl":"https://aihot.virxact.com/items/cmso8nqa70eq4rofw24w1wlwt","publishedAt":"2026-08-11T05:44:38.000Z","category":"行业动态","score":72,"selected":true,"articleBody":["In this tutorial, we implement an end-to-end MiniMax-H3 ：https://huggingface.co/Comfy-Org/MiniMax-H3 video generation workflow using ComfyUI as a headless inference backend. We configure the environment around GPU memory, disk capacity, model precision, resolution, duration, sampling strategy, and multiple generation modes, while dynamically selecting an appropriate weight profile based on the available hardware. We install and launch ComfyUI programmatically, download the required diffusion, text-encoder, video-VAE, and audio-VAE weights from Hugging Face, and communicate with the running server through its HTTP and WebSocket APIs. We also construct the ComfyUI execution graph directly in Python, validate node schemas against the live /object_info endpoint, and support text-to-video, first- and last-frame-conditioned generation, and reference-image-conditioned generation. By combining automated model setup, schema-aware graph construction, joint video-audio decoding, progress monitoring, and output collection, we create a reproducible pipeline for experimenting with MiniMax-H3 without relying on the graphical ComfyUI interface.","We define the core MiniMax-H3 configuration, model profiles, generation parameters, and shared utility functions used throughout the workflow. We calculate valid frame counts and canvas dimensions while checking GPU capability, available VRAM, BF16 support, and disk space before inference begins. We also automatically select the most appropriate model profile so the pipeline matches the hardware available in our Colab runtime.","We install and configure ComfyUI, prepare the external model directory structure, and enable MiniMax-H3 support inside the Colab environment. We download the required diffusion model, text encoder, video VAE, and audio VAE weights from Hugging Face while reusing cached files whenever possible. We also optionally retrieve the Turbo LoRA configuration, allowing us to trade some generation quality for faster inference when required.","We create a server-management layer that launches ComfyUI as a background subprocess and verifies that it becomes available through its API. We monitor server startup, inspect GPU memory statistics, free VRAM when necessary, and safely terminate the server after execution. We also build a schema-inspection utility that reads live ComfyUI node definitions so we can validate graph inputs and dynamically discover supported node slots.","We construct the MiniMax-H3 ComfyUI workflow graph entirely in Python using reusable node-building methods. We assemble the model backbone, conditioning pipeline, sampler, schedulers, joint latent decoding, video creation, and output-saving stages for both standard and Turbo configurations. We also support text-to-video, first- and last-frame-conditioned video, and reference-image-conditioned video generation through the same programmable graph architecture.","We handle image uploads, graph submission, WebSocket progress tracking, output discovery, and the tutorial’s complete execution flow. We submit the generated graph to ComfyUI, monitor individual node execution and sampling progress, collect the resulting video files, and display manageable outputs directly inside Colab. We finally coordinate all earlier components through the main function, taking the workflow from hardware preflight and model loading to synchronized MiniMax-H3 video and audio generation.","In conclusion, we implemented a complete programmable MiniMax-H3 inference pipeline that takes us from hardware validation and model acquisition to graph execution and final synchronized video-audio generation. We used ComfyUI as a headless server while controlling the entire workflow from Python, which gives us direct access to configuration, model loading, conditioning, sampling, decoding, server lifecycle management, and generated outputs. We also made the pipeline more robust by dynamically inspecting ComfyUI node schemas, adapting model profiles to available VRAM, aligning frame counts with MiniMax-H3 requirements, and supporting multiple conditioning modes through the same reusable architecture. By the end of the workflow, we have a flexible foundation that we can extend with different prompts, seeds, reference images, frame constraints, LoRA acceleration, resolutions, and sampling strategies while preserving a consistent and automated MiniMax-H3 generation process.","Need to partner with us for promoting your GitHub Repo OR Hugging Face Page OR Product Release OR Webinar etc.? Connect with us ：https://forms.gle/wbash1wF6efRj8G58","Sana Hassan, a consulting intern at Marktechpost and dual-degree student at IIT Madras, is passionate about applying technology and AI to address real-world challenges. With a keen interest in solving practical problems, he brings a fresh perspective to the intersection of AI and real-life solutions."],"articleImages":[{"sourceUrl":"https://www.marktechpost.com/wp-content/uploads/2026/08/blog61912-9-100x70.png","alt":"webAI Releases TwIL-LM: A 1.7B and 3B Formal-Logic Model Family for Autoformalization on Local Hardware","afterParagraph":8,"url":"/media/articles/cmso8nqa70eq4rofw24w1wlwt/f481218a65418369.webp"},{"sourceUrl":"https://www.marktechpost.com/wp-content/uploads/2026/08/blog61912-7-100x70.png","alt":"Meta AI Releases Muse Glimmer: A 30B Open-Weights Agentic Model That Runs on One Consumer GPU","afterParagraph":8,"url":"/media/articles/cmso8nqa70eq4rofw24w1wlwt/f0c54674efc463c8.webp"},{"sourceUrl":"https://www.marktechpost.com/wp-content/uploads/2026/08/blog61912-6-100x70.png","alt":"ByteDance Seed Introduces SeedRealtime","afterParagraph":8,"url":"/media/articles/cmso8nqa70eq4rofw24w1wlwt/b3cae156694b5e86.webp"},{"sourceUrl":"https://www.marktechpost.com/wp-content/uploads/2026/08/blog61912-4-100x70.png","alt":"Top LLM Observability and Evaluation Platforms in 2026","afterParagraph":8,"url":"/media/articles/cmso8nqa70eq4rofw24w1wlwt/e2b8a442e6bcbcf7.webp"},{"sourceUrl":"https://www.marktechpost.com/wp-content/uploads/2026/08/blog61912-3-100x70.png","alt":"IMDb Sentiment Analysis with DistilBERT LoRA, TF-IDF Baselines, Calibration, Interpretability, Robustness Testing, and Semi-Supervised Learning","afterParagraph":8,"url":"/media/articles/cmso8nqa70eq4rofw24w1wlwt/24fbc864dc8ac57e.webp"}],"mediaStatus":"ok","articleBodyZh":["在本教程中，我们使用 ComfyUI 作为无头推理后端，实现端到端的 MiniMax-H3 视频生成工作流程：https://huggingface.co/Comfy-Org/MiniMax-H3。我们围绕 GPU 内存、磁盘容量、模型精度、分辨率、时长、采样策略和多种生成模式配置环境，同时根据可用硬件动态选择合适的权重配置。我们以编程方式安装并启动 ComfyUI，从 Hugging Face 下载所需的扩散模型、文本编码器、视频 VAE 和音频 VAE 权重，并通过其 HTTP 和 WebSocket API 与运行中的服务器通信。我们还直接在 Python 中构建 ComfyUI 执行图，验证节点模式是否与实时 /object_info 端点匹配，并支持文本到视频、首尾帧条件生成以及参考图像条件生成。通过结合自动化模型设置、模式感知图构建、联合视频-音频解码、进度监控和输出收集，我们创建了一个可重复的流水线，用于在不依赖 ComfyUI 图形界面的情况下试验 MiniMax-H3。","我们定义了核心的 MiniMax-H3 配置、模型配置文件、生成参数以及在整个工作流中使用的共享实用函数。在推理开始之前，我们计算有效帧数和画布尺寸，同时检查 GPU 能力、可用显存、BF16 支持以及磁盘空间。我们还会自动选择最合适的模型配置，以使流水线与 Colab 运行时可用的硬件匹配。","我们安装并配置 ComfyUI，准备外部模型目录结构，并在 Colab 环境中启用 MiniMax-H3 支持。我们从 Hugging Face 下载所需的扩散模型、文本编码器、视频 VAE 和音频 VAE 权重，同时尽可能重用缓存文件。我们还可以选择性地获取 Turbo LoRA 配置，使我们在需要时可以以稍微降低生成质量换取更快的推理速度。","我们创建了一个服务器管理层，它可以将 ComfyUI 作为后台子进程启动，并验证其通过 API 可用。我们监控服务器启动情况，检查 GPU 内存统计，必要时释放显存，并在执行完成后安全地终止服务器。我们还构建了一个模式检查工具，用于读取实时 ComfyUI 节点定义，以便验证图形输入并动态发现支持的节点槽。","我们完全使用 Python 构建 MiniMax-H3 ComfyUI 工作流程图，采用可重用的节点构建方法。我们组装模型主干、条件处理管线、采样器、调度器、联合潜在解码、视频创建和输出保存阶段，适用于标准和 Turbo 配置。我们还通过同一可编程图结构支持文本到视频、首尾帧条件视频，以及参考图像条件视频生成。","我们处理图像上传、图形提交、WebSocket 进度跟踪、输出发现以及教程的完整执行流程。我们将生成的图形提交给 ComfyUI，监控各个节点的执行和采样进度，收集生成的视频文件，并在 Colab 内直接显示可管理的输出。最终，我们通过主函数协调所有前述组件，将工作流程从硬件预检查和模型加载延伸到同步生成 MiniMax-H3 视频和音频。","总之，我们实现了一个完整的可编程 MiniMax-H3 推理管道，从硬件验证和模型获取，到图执行，再到最终同步的视频-音频生成。我们使用 ComfyUI 作为无头服务器，同时从 Python 控制整个工作流，这使我们可以直接访问配置、模型加载、条件设置、采样、解码、服务器生命周期管理以及生成的输出。我们还通过动态检查 ComfyUI 节点模式、将模型配置适配到可用显存、使帧数与 MiniMax-H3 要求对齐，并通过相同的可复用架构支持多种条件模式，使该管道更加稳健。在工作流结束时，我们获得了一个灵活的基础，可以使用不同的提示、种子、参考图像、帧约束、LoRA 加速、分辨率和采样策略进行扩展，同时保持一致且自动化的 MiniMax-H3 生成过程。","需要与我们合作以推广您的 GitHub 仓库或 Hugging Face 页面或产品发布或网络研讨会等？请联系我们：https://forms.gle/wbash1wF6efRj8G58","Sana Hassan 是 Marktechpost 的咨询实习生，同时也是印度理工学院马德拉斯分校的双学位学生，他热衷于将技术和人工智能应用于解决实际问题。对解决实际问题有浓厚兴趣的他，为 AI 与现实解决方案的交汇带来了新的视角。"],"translationStatus":"translated","bodyOrigin":"source-page","editorial":{"summary":"Aioga 编辑摘要：本教程演示如何以 ComfyUI 为无头推理后端，构建端到端的 MiniMax-H3 视频生成工作流。 Aioga 将其归入「行业动态」方向，重点关注它对真实使用和行业竞争的影响。","background":"背景分析：公司与行业类动态需要放在竞争格局、商业化路径、资本信号和监管环境中观察，单条公告不能代表最终结果。","viewpoint":"Aioga 判断：这条动态更适合作为行业观察信号，当前信息足以建立线索，但不足以推导长期结论。","implications":"影响分析：对相关团队而言，短期应先核对来源、可用范围和实际成本，再判断是否值得接入或跟进。","nextStep":"后续观察：继续观察官方文件、合作落地、收入或用户信号、竞品动作和监管后续。","evidenceRefs":["title","summary","articleBody"],"confidence":"medium","status":"published","aiGenerated":false,"autoApproved":true,"generatedBy":"rule-safe-fallback","generatedAt":"2026-08-11T11:23:41.956Z","sourceHash":"7b08cbc1c686f27f","validation":{"passed":true,"mode":"rule-safe-fallback","checks":["schema","length","source-attribution","no-html"]}},"tags":["行业动态","MarkTechPost（RSS）"],"translations":{"zh-CN":{"title":"用 ComfyUI API 实现 MiniMax-H3 多模态视频与音频生成流水线","summary":"本教程演示如何以 ComfyUI 为无头推理后端，构建端到端的 MiniMax-H3 视频生成工作流。通过 Python 直接构建执行图，支持文生视频、首尾帧条件生成和参考图像条件生成，并自动根据 GPU 显存选择 quality、balanced、squeeze 三种权重配置。流水线涵盖模型自动下载、节点模式校验、音视频联合解码与进度监控，无需图形界面即可复现实验。 🔗 阅读原文 via AIHOT · https://aihot.virxact.com/items/cmso8nqa70eq4rofw24w1wlwt","category":"行业动态","source":"marktechpost.com","aggregationSource":"MarkTechPost（RSS）","pageTitle":"用 ComfyUI API 实现 MiniMax-H3 多模态视频与音频生成流水线 - Aioga AI资讯","description":"本教程演示如何以 ComfyUI 为无头推理后端，构建端到端的 MiniMax-H3 视频生成工作流。通过 Python 直接构建执行图，支持文生视频、首尾帧条件生成和参考图像条件生成，并自动根据 GPU 显存选择 quality、balanced、squeeze 三种权重配置。流水线涵盖模型自动下载、节点模式校验、音视频联合解码与进度监控，无需图形界面即可...","url":"https://www.aioga.com/news/cmso8nqa70eq4rofw24w1wlwt/","articleBody":["在本教程中，我们使用 ComfyUI 作为无头推理后端，实现端到端的 MiniMax-H3 视频生成工作流程：https://huggingface.co/Comfy-Org/MiniMax-H3。我们围绕 GPU 内存、磁盘容量、模型精度、分辨率、时长、采样策略和多种生成模式配置环境，同时根据可用硬件动态选择合适的权重配置。我们以编程方式安装并启动 ComfyUI，从 Hugging Face 下载所需的扩散模型、文本编码器、视频 VAE 和音频 VAE 权重，并通过其 HTTP 和 WebSocket API 与运行中的服务器通信。我们还直接在 Python 中构建 ComfyUI 执行图，验证节点模式是否与实时 /object_info 端点匹配，并支持文本到视频、首尾帧条件生成以及参考图像条件生成。通过结合自动化模型设置、模式感知图构建、联合视频-音频解码、进度监控和输出收集，我们创建了一个可重复的流水线，用于在不依赖 ComfyUI 图形界面的情况下试验 MiniMax-H3。","我们定义了核心的 MiniMax-H3 配置、模型配置文件、生成参数以及在整个工作流中使用的共享实用函数。在推理开始之前，我们计算有效帧数和画布尺寸，同时检查 GPU 能力、可用显存、BF16 支持以及磁盘空间。我们还会自动选择最合适的模型配置，以使流水线与 Colab 运行时可用的硬件匹配。","我们安装并配置 ComfyUI，准备外部模型目录结构，并在 Colab 环境中启用 MiniMax-H3 支持。我们从 Hugging Face 下载所需的扩散模型、文本编码器、视频 VAE 和音频 VAE 权重，同时尽可能重用缓存文件。我们还可以选择性地获取 Turbo LoRA 配置，使我们在需要时可以以稍微降低生成质量换取更快的推理速度。","我们创建了一个服务器管理层，它可以将 ComfyUI 作为后台子进程启动，并验证其通过 API 可用。我们监控服务器启动情况，检查 GPU 内存统计，必要时释放显存，并在执行完成后安全地终止服务器。我们还构建了一个模式检查工具，用于读取实时 ComfyUI 节点定义，以便验证图形输入并动态发现支持的节点槽。","我们完全使用 Python 构建 MiniMax-H3 ComfyUI 工作流程图，采用可重用的节点构建方法。我们组装模型主干、条件处理管线、采样器、调度器、联合潜在解码、视频创建和输出保存阶段，适用于标准和 Turbo 配置。我们还通过同一可编程图结构支持文本到视频、首尾帧条件视频，以及参考图像条件视频生成。","我们处理图像上传、图形提交、WebSocket 进度跟踪、输出发现以及教程的完整执行流程。我们将生成的图形提交给 ComfyUI，监控各个节点的执行和采样进度，收集生成的视频文件，并在 Colab 内直接显示可管理的输出。最终，我们通过主函数协调所有前述组件，将工作流程从硬件预检查和模型加载延伸到同步生成 MiniMax-H3 视频和音频。","总之，我们实现了一个完整的可编程 MiniMax-H3 推理管道，从硬件验证和模型获取，到图执行，再到最终同步的视频-音频生成。我们使用 ComfyUI 作为无头服务器，同时从 Python 控制整个工作流，这使我们可以直接访问配置、模型加载、条件设置、采样、解码、服务器生命周期管理以及生成的输出。我们还通过动态检查 ComfyUI 节点模式、将模型配置适配到可用显存、使帧数与 MiniMax-H3 要求对齐，并通过相同的可复用架构支持多种条件模式，使该管道更加稳健。在工作流结束时，我们获得了一个灵活的基础，可以使用不同的提示、种子、参考图像、帧约束、LoRA 加速、分辨率和采样策略进行扩展，同时保持一致且自动化的 MiniMax-H3 生成过程。","需要与我们合作以推广您的 GitHub 仓库或 Hugging Face 页面或产品发布或网络研讨会等？请联系我们：https://forms.gle/wbash1wF6efRj8G58","Sana Hassan 是 Marktechpost 的咨询实习生，同时也是印度理工学院马德拉斯分校的双学位学生，他热衷于将技术和人工智能应用于解决实际问题。对解决实际问题有浓厚兴趣的他，为 AI 与现实解决方案的交汇带来了新的视角。"]},"en":{"title":"Implementing MiniMax-H3 Multimodal Video and Audio Generation Pipeline Using ComfyUI API","summary":"This tutorial demonstrates how to use ComfyUI as a headless inference backend to build an end-to-end MiniMax-H3 video generation workflow. By constructing the execution graph directly through Python, it supports text-to-video generation, first-and-last frame conditional generation, and reference image conditional generation, while automatically selecting one of three weight configurations—quality, balanced, or squeeze—based on GPU memory. The pipeline includes automatic model downloading, node mode validation, audio-video joint decoding, and progress monitoring, allowing experiments to be reproduced without a graphical interface. 🔗 Read the original via AIHOT · https://aihot.virxact.com/items/cmso8nqa70eq4rofw24w1wlwt","category":"Industry","source":"MarkTechPost（RSS）","aggregationSource":"MarkTechPost（RSS）","pageTitle":"Implementing MiniMax-H3 Multimodal Video and Audio Generation Pipeline Using ComfyUI API - Aioga AI News","description":"This tutorial demonstrates how to use ComfyUI as a headless inference backend to build an end-to-end MiniMax-H3 video generation workflow. By constructing the execution graph direc...","url":"https://www.aioga.com/en/news/cmso8nqa70eq4rofw24w1wlwt/","contentTranslated":true,"sourceHash":"d7c4db69d6a2ef47","translatedAt":"2026-08-11T10:43:43.566Z"},"ja":{"title":"ComfyUI API を使って MiniMax-H3 のマルチモーダル動画および音声生成パイプラインを実現する","summary":"本チュートリアルでは、ComfyUI をヘッドレス推論バックエンドとして使用し、エンドツーエンドの MiniMax-H3 ビデオ生成ワークフローを構築する方法を示します。Python を使って直接実行グラフを構築でき、テキストからビデオ生成、先頭・末尾フレーム条件生成、参照画像条件生成に対応し、GPU メモリに応じて quality、balanced、squeeze の三種類の重み設定を自動で選択します。パイプラインにはモデル自動ダウンロード、ノードモード検証、オーディオ・ビデオの共通デコードと進行状況監視が含まれ、GUI なしで実験を再現可能です。 🔗 原文はこちら via AIHOT · https://aihot.virxact.com/items/cmso8nqa70eq4rofw24w1wlwt","category":"業界動向","source":"MarkTechPost（RSS）","aggregationSource":"MarkTechPost（RSS）","pageTitle":"ComfyUI API を使って MiniMax-H3 のマルチモーダル動画および音声生成パイプラインを実現する - Aioga AIニュース","description":"本チュートリアルでは、ComfyUI をヘッドレス推論バックエンドとして使用し、エンドツーエンドの MiniMax-H3 ビデオ生成ワークフローを構築する方法を示します。Python を使って直接実行グラフを構築でき、テキストからビデオ生成、先頭・末尾フレーム条件生成、参照画像条件生成に対応し、GPU メモリに応じて quality、balanced、squ...","url":"https://www.aioga.com/ja/news/cmso8nqa70eq4rofw24w1wlwt/","contentTranslated":true,"sourceHash":"d7c4db69d6a2ef47","translatedAt":"2026-08-11T10:43:54.564Z"},"ko":{"title":"ComfyUI API를 사용하여 MiniMax-H3 다중 모달 비디오 및 오디오 생성 파이프라인 구현","summary":"이 튜토리얼은 ComfyUI를 헤드리스 추론 백엔드로 사용하여 엔드투엔드 MiniMax-H3 비디오 생성 워크플로우를 구축하는 방법을 보여줍니다. Python을 통해 직접 실행 그래프를 구축할 수 있으며, 텍스트-투-비디오, 시작 및 종료 프레임 조건 생성, 참조 이미지 조건 생성 등을 지원하고, GPU VRAM에 따라 quality, balanced, squeeze 세 가지 가중치 구성을 자동으로 선택합니다. 파이프라인에는 모델 자동 다운로드, 노드 모드 검증, 오디오·비디오 공동 디코딩 및 진행 상황 모니터링이 포함되어 있어, 그래픽 인터페이스 없이도 실험을 재현할 수 있습니다. 🔗 원문 보기 via AIHOT · https://aihot.virxact.com/items/cmso8nqa70eq4rofw24w1wlwt","category":"업계 동향","source":"MarkTechPost（RSS）","aggregationSource":"MarkTechPost（RSS）","pageTitle":"ComfyUI API를 사용하여 MiniMax-H3 다중 모달 비디오 및 오디오 생성 파이프라인 구현 - Aioga AI 뉴스","description":"이 튜토리얼은 ComfyUI를 헤드리스 추론 백엔드로 사용하여 엔드투엔드 MiniMax-H3 비디오 생성 워크플로우를 구축하는 방법을 보여줍니다. Python을 통해 직접 실행 그래프를 구축할 수 있으며, 텍스트-투-비디오, 시작 및 종료 프레임 조건 생성, 참조 이미지 조건 생성 등을 지원하고, GPU VRAM에 따라...","url":"https://www.aioga.com/ko/news/cmso8nqa70eq4rofw24w1wlwt/","contentTranslated":true,"sourceHash":"d7c4db69d6a2ef47","translatedAt":"2026-08-11T10:44:45.272Z"},"es":{"title":"Implementación de la línea de producción de generación de video y audio multimodal MiniMax-H3 usando la API de ComfyUI","summary":"Este tutorial muestra cómo construir un flujo de trabajo de generación de video MiniMax-H3 de extremo a extremo usando ComfyUI como motor de inferencia sin cabeza. Se puede construir directamente el gráfico de ejecución con Python, soportando generación de video a partir de texto, generación condicionada por los cuadros inicial y final, y generación condicionada por imágenes de referencia, y selecciona automáticamente entre tres configuraciones de peso (quality, balanced, squeeze) según la memoria de la GPU. La canalización incluye descarga automática de modelos, verificación de modo de nodos, decodificación conjunta de audio y video, y monitoreo de progreso, sin necesidad de una interfaz gráfica para reproducir los experimentos. 🔗 Leer el artículo original vía AIHOT · https://aihot.virxact.com/items/cmso8nqa70eq4rofw24w1wlwt","category":"Industria","source":"MarkTechPost（RSS）","aggregationSource":"MarkTechPost（RSS）","pageTitle":"Implementación de la línea de producción de generación de video y audio multimodal MiniMax-H3 usando la API de ComfyUI - Aioga Noticias de IA","description":"Este tutorial muestra cómo construir un flujo de trabajo de generación de video MiniMax-H3 de extremo a extremo usando ComfyUI como motor de inferencia sin cabeza. Se puede constru...","url":"https://www.aioga.com/es/news/cmso8nqa70eq4rofw24w1wlwt/","contentTranslated":true,"sourceHash":"d7c4db69d6a2ef47","translatedAt":"2026-08-11T10:44:42.912Z"},"fr":{"title":"Réaliser une chaîne de génération multimodale vidéo et audio MiniMax-H3 en utilisant l'API ComfyUI","summary":"Ce tutoriel montre comment utiliser ComfyUI comme backend de calcul sans interface graphique pour construire un flux de travail de génération vidéo MiniMax-H3 de bout en bout. Il permet de construire directement des graphes d'exécution en Python, supporte la génération de vidéos à partir de texte, la génération conditionnée par le premier et le dernier cadre, ainsi que la génération conditionnée par des images de référence, et sélectionne automatiquement parmi trois configurations de poids — quality, balanced, squeeze — en fonction de la mémoire GPU. Le pipeline couvre le téléchargement automatique des modèles, la vérification des modes des nœuds, le décodage audio et vidéo conjoint avec suivi de progression, permettant de reproduire les expériences sans interface graphique. 🔗 Lire l'article original via AIHOT · https://aihot.virxact.com/items/cmso8nqa70eq4rofw24w1wlwt","category":"Industrie","source":"MarkTechPost（RSS）","aggregationSource":"MarkTechPost（RSS）","pageTitle":"Réaliser une chaîne de génération multimodale vidéo et audio MiniMax-H3 en utilisant l'API ComfyUI - Aioga Actualités IA","description":"Ce tutoriel montre comment utiliser ComfyUI comme backend de calcul sans interface graphique pour construire un flux de travail de génération vidéo MiniMax-H3 de bout en bout. Il p...","url":"https://www.aioga.com/fr/news/cmso8nqa70eq4rofw24w1wlwt/","contentTranslated":true,"sourceHash":"d7c4db69d6a2ef47","translatedAt":"2026-08-11T10:45:47.886Z"},"de":{"title":"Implementierung einer Multi-Modal-Video- und Audioerzeugungspipeline MiniMax-H3 mit der ComfyUI-API","summary":"Dieses Tutorial zeigt, wie man ComfyUI als Headless-Inferenzbackend verwendet, um einen End-to-End MiniMax-H3 Videoerstellungs-Workflow aufzubauen. Durch direktes Erstellen von Ausführungsdiagrammen in Python werden Text-zu-Video, Frame-bedingte Generierung (Anfang und Ende) und Referenzbild-bedingte Generierung unterstützt, und automatisch wird basierend auf dem GPU-Videospeicher zwischen den Gewichtskonfigurationen quality, balanced und squeeze gewählt. Die Pipeline umfasst automatisches Herunterladen von Modellen, Knotenmodus-Überprüfung, gemeinsame Audio- und Video-Dekodierung sowie Fortschrittsüberwachung, sodass Experimente ohne grafische Benutzeroberfläche reproduziert werden können. 🔗 Originaltext lesen via AIHOT · https://aihot.virxact.com/items/cmso8nqa70eq4rofw24w1wlwt","category":"行业动态","source":"MarkTechPost（RSS）","aggregationSource":"MarkTechPost（RSS）","pageTitle":"Implementierung einer Multi-Modal-Video- und Audioerzeugungspipeline MiniMax-H3 mit der ComfyUI-API - Aioga KI-News","description":"Dieses Tutorial zeigt, wie man ComfyUI als Headless-Inferenzbackend verwendet, um einen End-to-End MiniMax-H3 Videoerstellungs-Workflow aufzubauen. Durch direktes Erstellen von Aus...","url":"https://www.aioga.com/de/news/cmso8nqa70eq4rofw24w1wlwt/","contentTranslated":true,"sourceHash":"d7c4db69d6a2ef47","translatedAt":"2026-08-11T10:45:37.724Z"},"pt-BR":{"title":"Implementando um pipeline de geração multimodal de vídeo e áudio MiniMax-H3 usando a API ComfyUI","summary":"Este tutorial demonstra como construir um fluxo de trabalho de geração de vídeo MiniMax-H3 de ponta a ponta, usando o ComfyUI como back-end de inferência sem cabeça. Ao construir diretamente o gráfico de execução em Python, ele suporta geração de vídeo a partir de texto, geração condicional com quadros inicial e final, e geração condicional com imagens de referência, além de selecionar automaticamente entre três configurações de peso - quality, balanced e squeeze - de acordo com a memória da GPU. O pipeline cobre download automático de modelos, verificação de modo de nó, decodificação conjunta de áudio e vídeo e monitoramento de progresso, permitindo reproduzir experimentos sem uma interface gráfica. 🔗 Leia o texto original via AIHOT · https://aihot.virxact.com/items/cmso8nqa70eq4rofw24w1wlwt","category":"行业动态","source":"MarkTechPost（RSS）","aggregationSource":"MarkTechPost（RSS）","pageTitle":"Implementando um pipeline de geração multimodal de vídeo e áudio MiniMax-H3 usando a API ComfyUI - Aioga Notícias de IA","description":"Este tutorial demonstra como construir um fluxo de trabalho de geração de vídeo MiniMax-H3 de ponta a ponta, usando o ComfyUI como back-end de inferência sem cabeça. Ao construir d...","url":"https://www.aioga.com/pt-BR/news/cmso8nqa70eq4rofw24w1wlwt/","contentTranslated":true,"sourceHash":"d7c4db69d6a2ef47","translatedAt":"2026-08-11T10:46:42.597Z"},"ru":{"title":"Реализация мультимодального видео- и аудиогенерационного конвейера MiniMax-H3 с использованием ComfyUI API","summary":"В этом руководстве показано, как использовать ComfyUI в качестве безголового вычислительного бэкенда для построения сквозного рабочего процесса генерации видео MiniMax-H3. С помощью Python можно напрямую строить граф выполнения, поддерживается генерация видео по тексту, генерация с условием на первые и последние кадры, а также генерация с условием на эталонное изображение, при этом автоматически выбирается одна из трёх конфигураций веса — quality, balanced или squeeze — в зависимости от объема видеопамяти GPU. Конвейер включает автоматическую загрузку моделей, проверку режима узлов, совместное декодирование аудио и видео и мониторинг прогресса, что позволяет воспроизводить эксперименты без графического интерфейса. 🔗 Читать оригинал через AIHOT · https://aihot.virxact.com/items/cmso8nqa70eq4rofw24w1wlwt","category":"行业动态","source":"MarkTechPost（RSS）","aggregationSource":"MarkTechPost（RSS）","pageTitle":"Реализация мультимодального видео- и аудиогенерационного конвейера MiniMax-H3 с использованием ComfyUI API - Aioga Новости ИИ","description":"В этом руководстве показано, как использовать ComfyUI в качестве безголового вычислительного бэкенда для построения сквозного рабочего процесса генерации видео MiniMax-H3. С помощь...","url":"https://www.aioga.com/ru/news/cmso8nqa70eq4rofw24w1wlwt/","contentTranslated":true,"sourceHash":"d7c4db69d6a2ef47","translatedAt":"2026-08-11T10:46:36.888Z"},"ar":{"title":"تنفيذ خط إنتاج توليد الفيديو والصوت متعدد الوسائط MiniMax-H3 باستخدام ComfyUI API","summary":"يوضح هذا الدرس كيفية استخدام ComfyUI كخلفية استدلال بدون واجهة رسومية لبناء سير عمل كامل لتوليد الفيديو MiniMax-H3. يمكن إنشاء مخطط التنفيذ مباشرة عبر Python، ويدعم توليد الفيديو من النص، والتوليد الشرطي بالإطار الأول والأخير، والتوليد الشرطي بالصور المرجعية، كما يقوم بتحديد إعدادات الوزن الثلاثة quality و balanced و squeeze تلقائيًا وفقًا لذاكرة GPU. يغطي خط الأنابيب التنزيل التلقائي للنماذج، والتحقق من نمط العقد، وفك ترميز الصوت والفيديو مع مراقبة التقدم، دون الحاجة إلى واجهة رسومية لإعادة إنتاج التجربة. 🔗 قراءة النص الأصلي عبر AIHOT · https://aihot.virxact.com/items/cmso8nqa70eq4rofw24w1wlwt","category":"行业动态","source":"MarkTechPost（RSS）","aggregationSource":"MarkTechPost（RSS）","pageTitle":"تنفيذ خط إنتاج توليد الفيديو والصوت متعدد الوسائط MiniMax-H3 باستخدام ComfyUI API - Aioga أخبار الذكاء الاصطناعي","description":"يوضح هذا الدرس كيفية استخدام ComfyUI كخلفية استدلال بدون واجهة رسومية لبناء سير عمل كامل لتوليد الفيديو MiniMax-H3. يمكن إنشاء مخطط التنفيذ مباشرة عبر Python، ويدعم توليد الفيديو م...","url":"https://www.aioga.com/ar/news/cmso8nqa70eq4rofw24w1wlwt/","contentTranslated":true,"sourceHash":"d7c4db69d6a2ef47","translatedAt":"2026-08-11T10:47:31.008Z"},"hi":{"title":"ComfyUI API का उपयोग करके MiniMax-H3 बहु-मोडल वीडियो और ऑडियो निर्माण पाइपलाइन को लागू करना","summary":"यह ट्यूटोरियल दिखाता है कि कैसे ComfyUI को हेडलेस इनफरेंस बैकएंड के रूप में उपयोग करके एंड-टू-एंड MiniMax-H3 वीडियो जनरेशन वर्कफ़्लो बनाया जाए। Python के माध्यम से सीधे एक्ज़िक्यूशन ग्राफ़ बनाना, टेक्स्ट-टू-विडियो, शुरुआती और अंतिम फ्रेम की कंडीशनल जनरेशन और संदर्भ चित्र की कंडीशनल जनरेशन को सपोर्ट करता है, और GPU मेमोरी के आधार पर quality, balanced, squeeze तीन वेट कॉन्फ़िगरेशन को स्वचालित रूप से चुनता है। पाइपलाइन में मॉडल का स्वचालित डाउनलोड, नोड मोड वेरिफिकेशन, ऑडियो और वीडियो का संयुक्त डिकोडिंग और प्रगति निगरानी शामिल है, जिससे ग्राफिकल इंटरफ़ेस की आवश्यकता के बिना प्रयोग को दोहराया जा सकता है। 🔗 मूल लेख पढ़ें via AIHOT · https://aihot.virxact.com/items/cmso8nqa70eq4rofw24w1wlwt","category":"行业动态","source":"MarkTechPost（RSS）","aggregationSource":"MarkTechPost（RSS）","pageTitle":"ComfyUI API का उपयोग करके MiniMax-H3 बहु-मोडल वीडियो और ऑडियो निर्माण पाइपलाइन को लागू करना - Aioga AI समाचार","description":"यह ट्यूटोरियल दिखाता है कि कैसे ComfyUI को हेडलेस इनफरेंस बैकएंड के रूप में उपयोग करके एंड-टू-एंड MiniMax-H3 वीडियो जनरेशन वर्कफ़्लो बनाया जाए। Python के माध्यम से सीधे एक्ज़िक्यूश...","url":"https://www.aioga.com/hi/news/cmso8nqa70eq4rofw24w1wlwt/","contentTranslated":true,"sourceHash":"d7c4db69d6a2ef47","translatedAt":"2026-08-11T10:47:37.370Z"},"it":{"title":"Realizzare una pipeline di generazione video e audio multimodale MiniMax-H3 utilizzando l'API ComfyUI","summary":"Questo tutorial mostra come utilizzare ComfyUI come backend di inferenza headless per costruire un flusso di lavoro end-to-end di generazione video MiniMax-H3. Permette di costruire direttamente un grafo di esecuzione tramite Python, supportando la generazione di video da testo, la generazione condizionata da frame iniziale e finale e la generazione condizionata da immagini di riferimento, selezionando automaticamente tra le configurazioni di peso quality, balanced e squeeze in base alla memoria GPU. La pipeline copre il download automatico dei modelli, la verifica della modalità dei nodi, il decodificatore audio-video combinato e il monitoraggio del progresso, permettendo di replicare gli esperimenti senza interfaccia grafica. 🔗 Leggi l'originale via AIHOT · https://aihot.virxact.com/items/cmso8nqa70eq4rofw24w1wlwt","category":"行业动态","source":"MarkTechPost（RSS）","aggregationSource":"MarkTechPost（RSS）","pageTitle":"Realizzare una pipeline di generazione video e audio multimodale MiniMax-H3 utilizzando l'API ComfyUI - Aioga Notizie IA","description":"Questo tutorial mostra come utilizzare ComfyUI come backend di inferenza headless per costruire un flusso di lavoro end-to-end di generazione video MiniMax-H3. Permette di costruir...","url":"https://www.aioga.com/it/news/cmso8nqa70eq4rofw24w1wlwt/","contentTranslated":true,"sourceHash":"d7c4db69d6a2ef47","translatedAt":"2026-08-11T10:48:31.459Z"},"nl":{"title":"MiniMax-H3 multimodale video- en audioproductiepipeline implementeren met de ComfyUI API","summary":"Deze tutorial demonstreert hoe je ComfyUI kunt gebruiken als een headless inferentie-backend om een end-to-end MiniMax-H3 videoproductieworkflow te bouwen. Door het uitvoeringsdiagram rechtstreeks met Python te maken, ondersteunt het tekst-naar-video, condities met eerste en laatste frame, en condities op basis van referentiebeelden, en selecteert automatisch de configuraties voor quality, balanced en squeeze afhankelijk van het GPU-geheugen. De pijplijn omvat automatische modeldownloads, verificatie van nodemodi, gezamenlijke audio- en video-decodering en voortgangsbewaking, zodat experimenten gereproduceerd kunnen worden zonder grafische interface. 🔗 Lees het originele artikel via AIHOT · https://aihot.virxact.com/items/cmso8nqa70eq4rofw24w1wlwt","category":"行业动态","source":"MarkTechPost（RSS）","aggregationSource":"MarkTechPost（RSS）","pageTitle":"MiniMax-H3 multimodale video- en audioproductiepipeline implementeren met de ComfyUI API - Aioga AI-nieuws","description":"Deze tutorial demonstreert hoe je ComfyUI kunt gebruiken als een headless inferentie-backend om een end-to-end MiniMax-H3 videoproductieworkflow te bouwen. Door het uitvoeringsdiag...","url":"https://www.aioga.com/nl/news/cmso8nqa70eq4rofw24w1wlwt/","contentTranslated":true,"sourceHash":"d7c4db69d6a2ef47","translatedAt":"2026-08-11T10:48:37.058Z"},"tr":{"title":"ComfyUI API Kullanarak MiniMax-H3 Çok Modlu Video ve Ses Üretim Hattını Gerçekleştirme","summary":"Bu eğitim, ComfyUI'yi başsız çıkarım (headless inference) arka ucu olarak kullanarak, uçtan uca MiniMax-H3 video üretim iş akışını nasıl oluşturacağınızı gösterir. Python ile doğrudan yürütme grafiği oluşturmayı destekler; metinden videoya, baş ve son kare koşullu üretim ve referans görüntü koşullu üretimi destekler ve GPU belleğine göre otomatik olarak quality, balanced ve squeeze olmak üzere üç farklı ağırlık yapılandırmasını seçer. İş akışı, model otomatik indirme, düğüm modu doğrulama, ses ve video birleştirilmiş çözümleme ve ilerleme takibini kapsar; grafik arayüzüne ihtiyaç duymadan deneyleri tekrar üretmenizi sağlar. 🔗 Orijinal yazıyı oku via AIHOT · https://aihot.virxact.com/items/cmso8nqa70eq4rofw24w1wlwt","category":"行业动态","source":"MarkTechPost（RSS）","aggregationSource":"MarkTechPost（RSS）","pageTitle":"ComfyUI API Kullanarak MiniMax-H3 Çok Modlu Video ve Ses Üretim Hattını Gerçekleştirme - Aioga AI Haberleri","description":"Bu eğitim, ComfyUI'yi başsız çıkarım (headless inference) arka ucu olarak kullanarak, uçtan uca MiniMax-H3 video üretim iş akışını nasıl oluşturacağınızı gösterir. Python ile doğru...","url":"https://www.aioga.com/tr/news/cmso8nqa70eq4rofw24w1wlwt/","contentTranslated":true,"sourceHash":"d7c4db69d6a2ef47","translatedAt":"2026-08-11T10:49:28.069Z"},"vi":{"title":"Sử dụng API ComfyUI để thực hiện quy trình tạo video và âm thanh đa phương thức MiniMax-H3","summary":"Hướng dẫn này trình bày cách sử dụng ComfyUI làm backend suy luận không giao diện, xây dựng luồng công việc tạo video MiniMax-H3 đầu-cuối. Xây dựng trực tiếp biểu đồ thực thi qua Python, hỗ trợ tạo video từ văn bản, tạo theo điều kiện khung đầu-cuối và tạo theo điều kiện hình ảnh tham khảo, đồng thời tự động chọn ba cấu hình trọng số quality, balanced, squeeze dựa trên bộ nhớ GPU. Quy trình bao gồm tự động tải mô hình, kiểm tra chế độ nút, giải mã âm thanh và hình ảnh kết hợp với giám sát tiến trình, không cần giao diện đồ họa vẫn có thể tái hiện thí nghiệm. 🔗 Đọc bản gốc qua AIHOT · https://aihot.virxact.com/items/cmso8nqa70eq4rofw24w1wlwt","category":"行业动态","source":"MarkTechPost（RSS）","aggregationSource":"MarkTechPost（RSS）","pageTitle":"Sử dụng API ComfyUI để thực hiện quy trình tạo video và âm thanh đa phương thức MiniMax-H3 - Tin tức AI Aioga","description":"Hướng dẫn này trình bày cách sử dụng ComfyUI làm backend suy luận không giao diện, xây dựng luồng công việc tạo video MiniMax-H3 đầu-cuối. Xây dựng trực tiếp biểu đồ thực thi qua P...","url":"https://www.aioga.com/vi/news/cmso8nqa70eq4rofw24w1wlwt/","contentTranslated":true,"sourceHash":"d7c4db69d6a2ef47","translatedAt":"2026-08-11T10:49:28.960Z"},"id":{"title":"Menggunakan ComfyUI API untuk mengimplementasikan alur produksi video dan audio multi-modal MiniMax-H3","summary":"Tutorial ini menunjukkan cara menggunakan ComfyUI sebagai backend inferensi headless untuk membangun alur kerja pembuatan video MiniMax-H3 ujung-ke-ujung. Dengan membangun grafik eksekusi langsung melalui Python, mendukung pembuatan video dari teks, pembuatan dengan kondisi frame awal dan akhir, serta pembuatan dengan kondisi gambar referensi, dan secara otomatis memilih konfigurasi bobot quality, balanced, squeeze berdasarkan VRAM GPU. Alur ini mencakup pengunduhan model otomatis, verifikasi mode node, dekode audio dan video bersama, serta pemantauan kemajuan, sehingga eksperimen dapat direproduksi tanpa antarmuka grafis. 🔗 Baca versi asli via AIHOT · https://aihot.virxact.com/items/cmso8nqa70eq4rofw24w1wlwt","category":"行业动态","source":"MarkTechPost（RSS）","aggregationSource":"MarkTechPost（RSS）","pageTitle":"Menggunakan ComfyUI API untuk mengimplementasikan alur produksi video dan audio multi-modal MiniMax-H3 - Berita AI Aioga","description":"Tutorial ini menunjukkan cara menggunakan ComfyUI sebagai backend inferensi headless untuk membangun alur kerja pembuatan video MiniMax-H3 ujung-ke-ujung. Dengan membangun grafik e...","url":"https://www.aioga.com/id/news/cmso8nqa70eq4rofw24w1wlwt/","contentTranslated":true,"sourceHash":"d7c4db69d6a2ef47","translatedAt":"2026-08-11T10:50:16.430Z"},"th":{"title":"ใช้ ComfyUI API เพื่อสร้างสายการผลิตวิดีโอและเสียงหลายโหมด MiniMax-H3","summary":"บทแนะนำนี้สาธิตวิธีใช้ ComfyUI เป็นแบ็กเอนด์สำหรับการอนุมานแบบ headless เพื่อสร้างเวิร์กโฟลว์การสร้างวิดีโอ MiniMax-H3 แบบครบวงจร สร้างกราฟการทำงานโดยตรงผ่าน Python รองรับการสร้างวิดีโอจากข้อความ การสร้างตามกรอบต้นและท้าย และการสร้างตามภาพอ้างอิง พร้อมปรับการตั้งค่าน้ำหนักสามแบบ quality, balanced, squeeze โดยอัตโนมัติตามหน่วยความจำ GPU เวิร์กโฟลว์ครอบคลุมการดาวน์โหลดโมเดลอัตโนมัติ การตรวจสอบโหมดของโหนด การถอดรหัสเสียงและวิดีโอร่วมกัน และการติดตามความคืบหน้า โดยไม่ต้องใช้ส่วนต่อประสานกราฟิกก็สามารถทำซ้ำการทดลองได้ 🔗 อ่านฉบับเต็ม via AIHOT · https://aihot.virxact.com/items/cmso8nqa70eq4rofw24w1wlwt","category":"行业动态","source":"MarkTechPost（RSS）","aggregationSource":"MarkTechPost（RSS）","pageTitle":"ใช้ ComfyUI API เพื่อสร้างสายการผลิตวิดีโอและเสียงหลายโหมด MiniMax-H3 - ข่าว AI Aioga","description":"บทแนะนำนี้สาธิตวิธีใช้ ComfyUI เป็นแบ็กเอนด์สำหรับการอนุมานแบบ headless เพื่อสร้างเวิร์กโฟลว์การสร้างวิดีโอ MiniMax-H3 แบบครบวงจร สร้างกราฟการทำงานโดยตรงผ่าน Python รองรับการสร้างว...","url":"https://www.aioga.com/th/news/cmso8nqa70eq4rofw24w1wlwt/","contentTranslated":true,"sourceHash":"d7c4db69d6a2ef47","translatedAt":"2026-08-11T10:50:24.094Z"},"pl":{"title":"Wykorzystanie API ComfyUI do realizacji wielomodalnego strumienia generowania wideo i audio MiniMax-H3","summary":"Ten samouczek pokazuje, jak użyć ComfyUI jako bezgłowego backendu do wnioskowania, aby zbudować kompleksowy przepływ pracy generowania wideo MiniMax-H3. Poprzez bezpośrednie budowanie grafu wykonywania w Pythonie, obsługuje generowanie wideo z tekstu, generowanie warunkowe na podstawie pierwszej i ostatniej klatki oraz generowanie warunkowe na podstawie obrazu referencyjnego, a automatycznie wybiera konfiguracje wag quality, balanced i squeeze w zależności od pamięci GPU. Pipeline obejmuje automatyczne pobieranie modeli, weryfikację trybów węzłów, wspólne dekodowanie audio i wideo oraz monitorowanie postępu, pozwalając odtwarzać eksperyment bez interfejsu graficznego. 🔗 Przeczytaj oryginał via AIHOT · https://aihot.virxact.com/items/cmso8nqa70eq4rofw24w1wlwt","category":"行业动态","source":"MarkTechPost（RSS）","aggregationSource":"MarkTechPost（RSS）","pageTitle":"Wykorzystanie API ComfyUI do realizacji wielomodalnego strumienia generowania wideo i audio MiniMax-H3 - Aioga Wiadomości AI","description":"Ten samouczek pokazuje, jak użyć ComfyUI jako bezgłowego backendu do wnioskowania, aby zbudować kompleksowy przepływ pracy generowania wideo MiniMax-H3. Poprzez bezpośrednie budowa...","url":"https://www.aioga.com/pl/news/cmso8nqa70eq4rofw24w1wlwt/","contentTranslated":true,"sourceHash":"d7c4db69d6a2ef47","translatedAt":"2026-08-11T10:51:17.119Z"}}}}