AI · alternatives · 2026

24 alternatives to Chess-LLM, using constrained-generation to force LLMs to battle it out

As I was playing with the Outlines library (https://outlines-dev.github.io/outlines/), I discussed with my friend Maxime how funny it would be if we set up a way to pair LLMs in chess matches till one wins. The first time I tried it, it required substantial prompt engineering to get some of those LLMs to propose valid moves. Large language models can mostly stay focused and even play rather well; see https://news.ycombinator.com/item?id=37616170 for example. However small language models aren't as easy to convince. Some of those LLMs have seen very little…

Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Chess-LLM, using constrained-generation to force LLMs to battle it out launched in 2024; newer entries below may have overtaken it.

1
I built a tiny LLM to demystify how language models work▲915
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 →
2
ChessGPT▲72
Unbeatable chess bot
2023 · chessgpt.ai · its alternatives →
3HL
How LLMs Work – Interactive visual guide based on Karpathy's lecture▲245
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 →
4
2000 Large Language Models (LLM) Prompts▲106
Unlock your knowledge with 2000 LLM prompts
2023 · miguelanticonam.gumroad.com · its alternatives →
5
I taught LLMs to play Magic: The Gathering against each other▲117
I've been teaching LLMs to play Magic: The Gathering recently, via MCP tools hooked up to the open-source XMage codebase. It's still pretty buggy and I think there's significant room for existing models to get better at it via tooling improvements, but it pretty much works today. The ratings for expensive frontier models are artificially low right now because I've been focusing on cheaper models until I work out the bugs, so they don't have a lot of games in the system.
Feb 2026 · mage-bench.com · its alternatives →
6IW
I wrapped the Zorks with an LLM▲111
I grew up on the Infocom games and when microsoft actually open-sourced Zork 1/2/3 I really wanted to figure out how to use LLMs to let you type whatever you want, I always found the amount language that the games "understood" to be so limiting - even if it was pretty state of the art at the time. So I figured out how to wrap it with Tambo.. (and run the game engine in the browser) basically whatever you type gets "translated" into zork-speak and passed to the game - and then the LLM takes the game's output and optionally adds flavor. (the little ">_" button at the top exposes the…
Jan 2026 · infocom.tambo.co · its alternatives →
7PP
Play poker with LLMs, or watch them play against each other▲163
I was curious to see how some of the latest models behaved and played no limit texas holdem. I built this website which allows you to: Spectate: Watch different models play against each other. Play: Create your own table and play hands against the agents directly.
Jan 2026 · llmholdem.com · its alternatives →
8
Faster LLM evaluation with Bayesian optimization▲131
Recently I've been working on making LLM evaluations fast by using bayesian optimization to select a sensible subset. Bayesian optimization is used because it’s good for exploration / exploitation of expensive black box (paraphrase, LLM). I would love to hear your thoughts and suggestions on this!
2024 · github.com · its alternatives →
9
LLM Prompt & Model Playground▲89
Test LLM prompts & models side-by-side against many inputs
2024 · its alternatives →
10
Recursive LLM Prompts▲97
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 →
11
Fine-grained stylistic control of LLMs using model arithmetic▲85
We developed a new framework that enables flexible control of generated text in language models. By combining several models and/or system prompts in one mathematical formula, it lets you tweak your style and combine model outputs with ease. A handy tool for those working with LLMs, looking for more fine-grained control of stylistic output. More details in our paper: https://arxiv.org/abs/2311.14479. Feedback and potential applications are welcome.
2023 · github.com · its alternatives →
12LA
llmgame.ai – The Wikipedia Game but with LLMs▲28
I used to play the Wikipedia Game in high school and had an idea for applying the same mechanic of clicking from concept to concept to LLMs. Will post another version that runs with an LLM entirely in the browser soon, but for now, please enjoy as long as my credits last... Warning: the LLM does not always cooperate
Jan 2026 · llmgame.ai · its alternatives →
13
Prompt Engine – Auto pick LLMs based on your prompts▲93
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 →
14
LLMWare – Small Specialized Function Calling 1B LLMs for Multi-Step RAG▲51
Hi, I was a corporate lawyer for many years working with a lot of financial services and insurance companies. In practicing law, I noticed there was a lot of repetition in the tasks I was working on even as a highly paid attorney that could be automated. I wanted to solve the problem of dealing with a lot information and data in a practical way, using AI. This motivated me to start AI Bloks/LLMWare with my husband, who had a deep background in software and is a very early adopter of AI. We have been on this journey with our open source project LLMWare for the past 4 months, producing a…
2024 · github.com · its alternatives →
15
Find the Best LLM for Your Needs▲33
Find the Best LLM for Your Needs through E2E Testing - Yuyz0112/relia
2024 · github.com · its alternatives →
16
LLM, a Rust Crate/CLI for CPU Inference of LLMs (LLaMA, GPT-NeoX, etc.)▲45
G'day, HN! I'm one of the maintainers of `llm`. I've been working alongside a trusty group of contributors to bring this project to life, and we're now at a point where we're ready to share it with the world. Large language models (LLMs) are taking the computing world by storm due to their emergent abilities that allow them to perform a wide variety of tasks, including translation, summarization, code generation, and even some degree of reasoning. However, the ecosystem around LLMs is still in its infancy, and it can be difficult to get started with these models. `llm` is a one-stop shop for…
2023 · github.com · its alternatives →
17
Watch LLMs play 21,000 hands of Poker▲36
PokerBench is my attempt at a new LLM benchmark wherein frontier models play Texas Hold'em in an arena setting. It also features a simulator to view individual games and observe how the different models reason about poker strategy. Opus/Haiku, Gemini Pro/Flash, GPT-5.2/5 mini, and Grok 4.1 Fast Reasoning have all been included. All code -> https://github.com/JoeAzar/pokerbench
Jan 2026 · pokerbench.adfontes.io · its alternatives →
18CG
Chessdream – Generate realistic chess positions with AI▲45
For no specific reason, I trained a neural network to generate random chess positions that look similar to positions from actual games (from lichess db). I also made it so you can condition it on some fixed pieces, and adjust the number of pieces. It turned out to be quite effective and I find it surprisingly fun and instructive to generate e.g. endgame positions with a certain pawn structure (set low temperature, place some pawns and position the kings, adjust number of pieces to get an endgame), and then figure out how to win vs. the computer in those positions. I hooked it up so that you…
2024 · chessdream.ai · its alternatives →
19
Improve Text-to-SQL Accuracy with LLM▲17
A repository that contains models, datasets, and fine-tuning techniques for DB-GPT, with the purpose of enhancing model performance in Text-to-SQL - eosphoros-ai/DB-GPT-Hub
2023 · github.com · its alternatives →
20
LLM Playground, compare results side by side▲14
Test and compare results from Large Language Models (LLMs) simultaneously, including Anthropic's Claude 1.2, OpenAI's GPT-4, GPT-3.5 turbo, and Cohere's CommandXL Nightly. Analyze the results side-by-side in a single UI on top of LLM APIs.
2023 · retool.com · its alternatives →
21
I made a state machine framework for guided conversations with LLMs▲19
It’s written in Python and I call it GoalChain. It lets you build a conversation flow graph that the user traverses. When there’s enough input it spits out a dictionary with the defined fields. Otherwise it will jump state to state as led by the user. It was fun to write, and it’s surprisingly effective if you keep in mind you’re prompt-engineering every string and field name. README.md has a mini-tutorial. Would be cool to get some ideas for how to build it further and what improvements I could make.
2024 · github.com · its alternatives →
22
Pokerbattle.ai – A week-long poker tournament for LLMs▲14
What PokerBattle.ai is a week-long live no-limit Texas Hold’em tournament where all players are top-tier reasoning LLMs. We’re testing how different models handle imperfect information and whether they can sustain consistent, math-driven poker without tool use or custom code. Why - In poker you can do well with basic math + consistent logic. - Superhuman poker AIs exist, but they rely on massive simulation/game-theory solvers and are effectively black boxes. - We want a rough, apples-to-apples comparison of LLM reasoning on poker decisions, and to collect public reasoning summaries that…
2025 · pokerbattle.ai · its alternatives →
23
LLMs can be susceptible to a new kind of malware▲17
New ways of breaking app-integrated LLMs . Contribute to greshake/llm-security development by creating an account on GitHub.
2023 · github.com · its alternatives →
24
Small LLM with Large Power▲14
2025 · github.com · its alternatives →

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