Six AI models played chess through their CLIs. None of them delivered checkmate.

A developer behind SpaceApp, a self-hosted workspace for running AI coding CLIs side by side, ran a six-model chess tournament on 18 October in which each model played through its own CLI. No game ended in checkmate; the standings were decided by forfeits, with Opus 5.5 (xhigh) and Gemini 4 Argon (High) tied at 3.5 points and 1535 Elo, while GPT-6-Astra, Fable 5.1, Gemini 3.8 Flash and GPT-6.1-Sol each forfeited two or three games. The developer said the run's real signal was reliability under deadlines — no timeouts, provider errors or illegal moves — which he called the property that matters most when agents run unattended for hours.

I build SpaceApp, a self-hosted workspace for running AI coding CLIs side by side. On 18 October I let six models play chess against each other there, each through its own CLI. Nobody won by checkmate. The way they lost is the interesting part. | | Model | Points | W / D / L | Elo | Avg per move | Forfeits | |---|---|---|---|---|---|---| | 1 | Opus 5.5 xhigh | 3.5 | 3 / 1 / 0 | 1535 | 13 s | 0 | | 2 | Gemini 4 Argon High | 3.5 | 3 / 1 / 0 | 1535 | 23 s | 0 | | 3 | GPT-6-Astra xhigh | 2 | 2 / 0 / 2 | 1500 | 37 s | 2 | | 4 | Fable 5.1 xhigh | 1 | 1 / 0 / 3 | 1478 | 26 s | 3 | | 5 | Gemini 3.8 Flash High | 1 | 1 / 0 / 3 | 1477 | 40 s | 3 | | 6 | GPT-6.1-Sol xhigh | 1 | 1 / 0 / 3 | 1475 | 34 s | 3 | Twelve games are a small sample, and a tournament decided by forfeits says very little about chess strength. What it does show is how reliably a model answers through its CLI when every answer has a deadline: no timeouts, no provider errors, no illegal moves, game after game. That is the property I care about most when agents run unattended for hours, and it is not the same ranking you get from a single-prompt leaderboard. SpaceApp runs on Linux, macOS and Windows 11 with Node.js 20.11 or newer: npx --yes run-spaceapp@latest install It is source-available under the Business Source License 1.1. Code, docs and known limitations: https://github.com/oll4com/spaceapp https://github.com/oll4com/spaceapp If you have run something similar, I would like to know which models held up for you, and which rules you would change for a fairer second run.