Riffusion
generalGenerative AI for creating and remixing music
General LLM tools include frameworks, APIs, evaluation utilities, and infrastructure specifically built around large language models. This category covers 369 tools that help developers build, test, fine-tune, and run applications on top of LLMs, from embedding calculators to full model-serving platforms.
Generative AI for creating and remixing music
Search and analyze video with AI
News monitoring and trend analytics for business teams
Turn text into short-form video
Create videos from text prompts
Writing assistant for authors and novelists
Upscale photos and create images from descriptions
Convert PDFs into interactive courses with adaptive quizzes
Launch, automate, and scale Meta ads from one dashboard
Convert long-form content into short social videos
Convert YouTube videos to blog posts
Generate sound effects with AI
Convert articles and text to video
Extract text from images and scanned docs
Online gaming platform
Generate videos with customizable templates
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Rewrite AI text to pass human detection
AI text generation in Spanish
Chat with custom AI characters and roleplay scenarios
Verify claims against reliable sources
Free tools for PDF, images, YouTube, and online utilities
Send SMS reminders before meetings to reduce no-shows
Free custom text wallpapers for devices and servers
This is a technically focused category aimed primarily at developers and ML engineers. Tools like Cognee and UpTrain address retrieval-augmented generation (RAG) pipelines and model evaluation, while platforms like Dstack and PeriFlow handle compute infrastructure for training and inference. Embedding Similarity Calculator and similar utilities fill narrow but useful gaps in LLM development workflows. OpenAssistant and Cerebras-GPT represent open-source or open-weight models that developers can run or fine-tune directly. When comparing options, consider whether a tool is model-agnostic or tied to a specific provider, and whether it supports the models you are already using. Latency, throughput, and cost-per-token are the metrics that matter most for production workloads. Evaluation tools are often underinvested in early projects but become critical once you are shipping to users. Many tools here are open source with paid managed versions, while others are closed SaaS products with usage-based pricing.