llms 18

This category covers tools built around large language models: infrastructure for deploying, fine-tuning, evaluating, and monitoring LLMs in production. With 369 tools listed, it is one of the more technical categories on the site, aimed primarily at developers and ML engineers rather than end users.

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AltText.ai

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AI alt text generator for images

Paid 43 · 53,696 votes

WordAi

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AI content rewriting and paraphrasing

Paid 42 · 42,649 votes

AIHumanizer.ai

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Transform AI-generated content to read more naturally

Paid 38 · 59,630 votes

SVG.io Migration to PicTrix

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SVG.io to PicTrix migration guide and membership mapping

Paid 37 · 53,947 votes

Undetected

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Make AI-generated text read more naturally and less robotic

Paid 37 · 52,779 votes

Podfy.ai

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Convert text and audio into edited videos automatically

Paid 37 · 40,796 votes

AI App Icon Generator

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Generate app icons from text descriptions

Paid 37 · 39,221 votes

Colorway AI

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Colors line art sketches and turns them into finished illustrations

Paid 37 · 37,526 votes

BEXI.ai

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Makes AI-generated text read like human writing

Paid 37 · 33,481 votes

CopyGenius

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Write product descriptions, ad copy, and blog outlines

Paid 35 · 13,787 votes

Yippity

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Turn notes into study decks with AI tutoring

Paid 35 · 13,422 votes

v0 report

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Business reporting with automated data analysis

Paid 34 · 7,393 votes

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Paid 32 · 62,731 votes

Preemedia

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Generate talking head videos from prompts

Paid 32 · 52,613 votes

AI Essay Writer

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AI tool to write and edit college essays

Paid 30 · 26,692 votes

AI Text Formatter

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Converts and formats AI-generated text for readability and usability

Paid 29 · 11,136 votes

TranscriptionPlus

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Fast AI transcription of audio and video

Paid 28 · 7,593 votes

tulz.AI

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AI audio transcription for multiple languages

Paid 27 · 4,361 votes

LLM tooling has exploded alongside the models themselves, and the category now spans several distinct problem areas. Deployment and serving tools like PeriFlow and Dstack help teams run models efficiently at scale. Evaluation and observability tools like UpTrain and AIWatch track model quality, drift, and cost over time. Memory and retrieval tools like Cognee add persistent context or RAG capabilities to LLM applications. When choosing, the key questions are infrastructure fit (cloud, on-prem, or hybrid), model compatibility (OpenAI-only vs. open-weight models), and whether the tool addresses your actual bottleneck, whether that is latency, cost, accuracy, or developer velocity. Pricing structures vary: some tools charge per token processed, others per seat or per API call. Open-source options exist across most sub-categories, which is worth considering for teams with engineering capacity to self-host.