AI · alternatives · 2026
24 alternatives to 2000 Large Language Models (LLM) Prompts
Unlock your knowledge with 2000 LLM prompts
This resource provides a collection of 2000 prompts designed for experimenting with large language models. It is intended for people interested in learning about LLMs and exploring their applications across different… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. 2000 Large Language Models (LLM) Prompts launched in 2023; newer entries below may have overtaken it.
- 1VI
Hi HN, We've just published a lot of original, visual, and intuitive explanations of concepts to introduce people to large language models. It's available for free with no sign-up needed and it includes text articles, some video explanations, and code examples/notebooks as well. And we're available to answer your questions in a dedicated Discord channel. You can find it here: https://llm.university/ Having written https://jalammar.github.io/illustrated-transformer/, I've been thinking about these topics and how best to communicate them for half a…
2023 · its alternatives →
- 2
Unlock your knowledge in machine learning
2023 · miguelanticonam.gumroad.com · its alternatives →
- 3
Built a ~9M param LLM from scratch to understand how they actually work. Vanilla transformer, 60K synthetic conversations, ~130 lines of PyTorch. Trains in 5 min on a free Colab T4. The fish thinks the meaning of life is food. Fork it and swap the personality for your own character.
Apr 2026 · github.com · its alternatives →
- 4HL
All content is based on Andrej Karpathy's "Intro to Large Language Models" lecture (youtube.com/watch?v=7xTGNNLPyMI). I downloaded the transcript and used Claude Code to generate the entire interactive site from it — single HTML file. I find it useful to revisit this content time to time.
Apr 2026 · ynarwal.github.io · its alternatives →
- 5
Nowadays, a common AI tech stack has hundreds of different prompts running across different LLMs. Three key problems: - Choices, picking from 100s of LLMs the best LLM for that 1 prompt is gonna be challenging, you're probably not picking the most optimized LLM for a prompt you wrote. - Scaling/Upgrading, similar to choices but you want to keep consistency of your output even when models depreciate or configurations change. - Prompt management is scary, if something works, you'll never want to touch it but you should be able to without fear of everything breaking. So we launched Prompt…
2024 · jigsawstack.com · its alternatives →
- 6
Test LLM prompts & models side-by-side against many inputs
2024 · its alternatives →
- 7
Promptology▲232AI prompt engineering business model guide
2023 · shushantlakhyani.gumroad.com · its alternatives →
- 8
- 9
I've been playing with the idea of an LLM prompt that causes the model to generate and return a new prompt. https://github.com/andyk/recursive_llm The idea I'm starting with is to implement recursion using English as the programming language and GPT as the runtime. It’s kind of like traditional recursion in code, but instead of having a function that calls itself with a different set of arguments, there is a prompt that returns itself with specific parts updated to reflect the new arguments. Here is a prompt for infinitely generating Fibonacci numbers: > You are a…
2023 · github.com · its alternatives →
- 10
Unlock your knowledge with 2000 API prompts
2023 · miguelanticonam.gumroad.com · its alternatives →
- 11
Unlock your knowledge with 2000 chatbot prompts
2023 · miguelanticonam.gumroad.com · its alternatives →
- 12
Compare AI models easily! All providers in one place. Find the best LLM for your needs with our comprehensive pricing calculator and feature comparison tool. OpenAI, Anthropic, Google, and more.
2024 · countless.dev · its alternatives →
- 13
Explore large language models in 512MB of RAM. Contribute to jncraton/languagemodels development by creating an account on GitHub.
2023 · github.com · its alternatives →
- 14TL
2023 · tinyllms.vercel.app · its alternatives →
- 15
An all-in-one blog for learning LLM ins and outs: tokenize, attention, PE, and more Project I've been diving deep into the internals of Large Language Models (LLMs) and started documenting my findings. My blog covers topics like: Tokenization techniques (e.g., BBPE) Attention mechanism (e.g. MHA, MQA, MLA) Positional encoding and extrapolation (e.g. RoPE, NTK-aware interpolation, YaRN) Architecture details of models like QWen, LLaMA Training methods including SFT and Reinforcement Learning If you're interested in the nuts and bolts of LLMs, feel free to check it out:…
2025 · comfyai.app · its alternatives →
- 16
- 17
https://medium.com/@theaniketgiri/three-months-ago-i-wanted-...
Oct 2025 · github.com · its alternatives →
- 18SP
I built a system that lets LLMs automatically learn and improve problem-solving strategies over time, inspired by Andrej Karpathy's idea of a "third paradigm" for LLM learning. The basic idea: instead of using static system prompts, the LLM builds up a database of strategies that actually work for different problem types. When you give it a new problem, it selects the most relevant strategies, applies them, then evaluates how well they worked and refines them. For example, after seeing enough word problems, it learned this strategy: 1) Read carefully and identify unknowns, 2) Define…
2025 · its alternatives →
- 19
Unlock your knowledge
2023 · miguelanticonam.gumroad.com · its alternatives →
- 20
- 21
Elevate your knowledge with no-code
2023 · miguelanticonam.gumroad.com · its alternatives →
- 22
Integrate LLMs into your product in minutes with AI's help
2023 · outset.ai · its alternatives →
- 23
Find the Best LLM for Your Needs through E2E Testing - Yuyz0112/relia
2024 · github.com · its alternatives →
- 24
A proof-of-concept language learning app that uses LLMs to generate definitions of unknown words using only previously mastered vocabulary.
Dec 2025 · simedw.com · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →