Six AI models played chess through their CLIs. None of them delivered checkmate.
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
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.
The setup
- Players: Opus 5.5 and Fable 5.1 (through Claude Code), GPT-6-Astra and GPT-6.1-Sol (through Codex), all at xhigh reasoning; Gemini 4 Argon (High) and Gemini 3.8 Flash (High) (through the Gemini CLI).
- Format: a 4-round Swiss tournament, 12 games.
- Clock: 120 seconds per move. Each move is one one-shot turn of the model's CLI: it gets the position and answers with a move.
- Strikes: a timeout, a provider error or a second illegal answer plays a random legal move for that side and counts a strike. The third strike forfeits the game.
- Length: after 60 plies (30 moves each) the game is adjudicated on material.
The results
| # | 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 |
- Zero checkmates. 11 of the 12 games ended on a third strike.
- The 12th game, Gemini 4 Argon against Opus 5.5, ran the full 60 plies and was drawn on material.
- Opus 5.5 and Gemini 4 Argon were the only models that never needed a fallback move. Opus 5.5 was also the fastest, at 13 seconds per move on average.
What it measures, and what it does not
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.
Try SpaceApp
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
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.
Originally published by Dev.to AI. Aggregated on AIWithGhost for educational purposes — full credit and traffic to the original publisher.