X-Me AI
generalGenerate avatar videos from text in 10 seconds
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.
Generate avatar videos from text in 10 seconds
Text-to-speech with 1,100+ voices in 80+ languages
Free custom text wallpapers for devices and servers
Extract summaries and key points from text
Create, translate, and resize on-brand images in 130+ languages
200+ AI tools in one app for text and image generation
AI code generation for.NET teams
Text to speech
Build forms from ideas using AI
Text to speech with 25+ voices
Data science programs in libraries
Learn Chinese by photographing text
Russian casino with free spins
Convert audio and video to text or subtitles, with summaries
Turn documents and text into flowcharts with AI
Text and video chat with strangers worldwide, no signup required
Create children's stories and therapeutic texts with AI
Summarize long-form text and extract key information
Information resource for craftui
Generate sound effects for videos and memes with AI
Transcription, speech-to-text, text-to-speech, dubbing, and live captions
Import products from Amazon and AliExpress to Shopify with AI
Automate Pinterest marketing and affiliate growth
Make AI-generated text sound natural and human-written
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.