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The exploitative poker solver. Built on real population data from millions of hands.

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Your AI pair programmer. With GitHub Copilot, get suggestions for whole lines or entire functions right inside your editor.

Which is more popular?
Based on our record, GitHub Copilot seems to be more popular. It has been mentioned 389 times since March 2021.
Website, pricing, platforms and company facts side by side.
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| Website | gtokiller.com | github.com |
| Pricing | — | |
| Company | Startup from España · 1 - 9 employees · 2025 | Startup from the United States |
| Listed in |
In their own words, as submitted to SaaSHub.


GTOkiller is an exploitative poker solver built on Mass Data Analysis (MDA). While GTO solvers compute strategies against a perfect opponent that doesn't exist, GTOkiller solves against how your player pool actually plays, measured across millions of real hands, and shows you exactly which leak...
Trained on billions of lines of public code, GitHub Copilot puts the knowledge you need at your fingertips, saving you time and helping you stay focused.
What each product offers, as listed by its team.


Possible disadvantages
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As answered by people managing GTOKiller and GitHub Copilot.
GTOKiller's answer
GTOkiller is an exploitative solver, not a GTO solver. GTO solvers compute strategies against a theoretically perfect opponent that doesn't exist in real games. GTOkiller computes the strategy that maximizes EV against the way your player pool actually plays, measured with Mass Data Analysis across millions of real hands. The exploitative layer is applied to the entire game tree simultaneously, and every deviation is auditable: you see the GTO baseline, the real population frequencies, and the exploit side by side.
GTOKiller's answer
GTOkiller was built by a small team of poker players and engineers in Spain who kept running into the same wall: hours of solver study that real opponents simply didn't respect. If the pool doesn't play GTO, a strictly better strategy must exist. They built the engine to compute it: mass data analysis over millions of real hands, turned into full-tree exploitative strategies with every number visible.
GTOKiller's answer
Compared to GTO solvers (GTO Wizard, PioSOLVER, GTO+): they teach you to play against an opponent that doesn't exist. Their exploitative features rely on manual nodelocking, which is theoretical, biased by your own assumptions, and limited to one node at a time. GTOkiller applies real population data to the full tree automatically, at roughly half the price of GTO Wizard's top tier.
GTOKiller's answer
A proprietary solving engine and a Mass Data Analysis pipeline processing millions of hands per pool, served through a web app built on Next.js and Google Cloud.
GTOKiller's answer
Individual online cash game professionals and regulars across Europe, North America and Latin America
GTOKiller's answer
Online cash game regulars at low and mid stakes (NL10 to NL100) who already study with solvers but feel their study doesn't translate into winrate, because their pools don't play anything close to GTO. Today the population data covers GG Poker NL10 to NL50; since leaks depend more on the stake than on the site, players at the same stakes on other sites use it as a close proxy.
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GitHub Copilot is a powerful tool that developers use to boost their productivity and streamline their coding process with the aid of AI.
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Recommendations tracked on public social media and blogs since March 2021.


Tracking GTOKiller since Jun 2026.
I build Browy, an open-source AI agent that lives In a Chrome side panel and a DevTools REPL. It drives the real browser Tabs you have open. The thing it does not have is its own subscription. It uses your existing GitHub Copilot... - Source: dev.to / 18 days ago
Snagly is a free, MIT-licensed set of 30 skills for AI coding agents — GitHub Copilot, Claude Code, Cursor, Codex and 70+ others — that turn "an AI that can drive a browser" into "an AI that tests like a QA professional." A skill, if you... - Source: dev.to / 2 months ago
Where llms.txt genuinely gets read is a different layer: coding and agent tooling — Cursor, Claude Code, GitHub Copilot, Windsurf — pulling a documentation site's pages with less token waste, plus emerging agent protocols like OpenAI's... - Source: dev.to / 4 months ago
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