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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.
Rent GPUs for AI, machine learning, and rendering
Voice generation and cloning from text
Create animated videos from images, text, or ideas
Get instant feedback on your writing to sound more natural
Make AI-generated text sound natural and human-like
Publish 50+ SEO-optimized articles monthly with full automation
Match similar names and addresses in databases
Adjust lighting in photos and videos with AI
4K AI video creation with lip sync
Rephrase text quickly and clearly
Auto-generate podcast summaries
Rewrite AI text to bypass detection
Convert typed text to realistic handwritten notes
Platform for publishing technical expertise to a global audience
AI motion generation for characters
Create custom sound effects from text descriptions
Voice-to-text that understands technical terms and jargon
Convert AI-written text to natural, human-sounding writing
Web search and semantic rerank API for LLM applications
Bypass AI detection with one click
Turn text descriptions into full-stack web apps
Convert text into short videos for YouTube and social media
AI code generation for.NET teams
Text and video chat with strangers worldwide, no signup required
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.