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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.
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Generate Excel formulas and analyze spreadsheets without coding
Long-form writing editor for storytellers
Turn text into memes with AI
Real-time speech translation with AI voices
Open-source rich text editor framework with extensions
Fast, open-source search and AI retrieval engine
Convert video to 3D animation instantly
Extract text from images with OCR
Search and analyze video with AI
Text-based RPG with AI dungeon master and world-building tools
Free AI sound effect generator from text
Browser with agentic AI that takes actions on your behalf
Listen to articles and PDFs
SEO-optimized blog posts from real data
Generate unique text for blogs, marketing, and writing projects
AI-powered ad creation with optimization for conversions
Create CSS animations using AI descriptions
AI regex generator and tester
AI assistant with web search and file integration
Write SEO-optimized blog content with ease
Summarize articles, PDFs, and videos instantly
Write and schedule posts for Twitter, LinkedIn, and Threads
Generate short videos from text prompts
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.