LOVO
generalText-to-speech with 500+ voices in 100 languages
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.
Text-to-speech with 500+ voices in 100 languages
Rewrite AI-generated text to sound human
Turn text into visual charts and infographics
Turn text prompts into AI-generated videos
Create videos with AI actors
Voice-to-text for Mac, Windows, iOS
App translation with full context and human review
Rewrite AI text to read like human writing
Fast translations across multiple languages
Portfolio platform with galleries and zero-commission sales
Voice-to-text transcription for notes and messages
Open-source rich text editor framework with extensions
Fast, open-source search and AI retrieval engine
AI-powered ad creation with optimization for conversions
AI regex generator and tester
AI assistant with web search and file integration
Extract text from images, PDFs, and handwritten notes
Make AI-generated text sound human and undetectable
Turn text into short-form video
Automate workflows across macOS apps
Write essays and homework with AI assistance
Convert AI text to human-sounding content for free
Make AI text read more naturally
Automate podcast editing and social clips
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.