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Game Trailer
RU
Enkhbayar's Olympiad Chess: Multi-Board Team Matches
Olympiad Chess evolves classical chess into a true 4v4 team esport. Across a shared central Source, pieces invade neighboring boards to flank opponents and rescue allies in synchronized team volleys. It's the world's first true multi-board competitive team chess.
- Release date
- Nov 5, 2026
- Platforms
- Windows
Price unavailable
Key details
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System requirements
Windows · from the game’s Steam page
Minimum
- ОС
- Windows 10 / 11 (64-bit)
- Процессор
- Quad-core CPU (Intel Core i3-6100 / AMD A10-9600P or equivalent)
- Оперативная память
- 4 GB ОЗУ
- Видеокарта
- Vulkan 1.0 or OpenGL ES 3.0 compatible GPU with up-to-date drivers (Intel HD 500 series / AMD Radeon equivalent)
- Сеть
- Широкополосное подключение к интернету
- Место на диске
- 1 GB
macOS
Minimum
- ОС
- macOS 10.15 or newer (64-bit)
- Процессор
- Intel Core i3 or Apple Silicon (M1 / M2 / M3 / M4)
- Оперативная память
- 4 GB ОЗУ
- Видеокарта
- Metal-capable integrated or dedicated graphics (Intel HD Graphics or Apple M-series integrated GPU)
- Сеть
- Широкополосное подключение к интернету
- Место на диске
- 1 GB
Linux
Minimum
- ОС
- Ubuntu 24.04+ (64-bit) or any modern Linux distribution with up-to-date Mesa drivers
- Процессор
- Quad-core CPU (Intel / AMD equivalent)
- Оперативная память
- 4 GB ОЗУ
- Видеокарта
- Vulkan-capable GPU with Mesa driver support (Integrated or dedicated Intel, AMD, or NVIDIA)
- Сеть
- Широкополосное подключение к интернету
- Место на диске
- 1 GB
The requirements are shown as Steam publishes them, in Russian.
EXPECTATION INTELLIGENCE
How anticipated is this game?
This is not an estimated wishlist count: the index uses the public Steam Popular Wishlist rank and verifiable signals.
limited dataconfidence 0%
Wishlist rank movementhigher on the chart means closer to first place
History will appear after several measurements
- Interest has not been measured: absence from the sample does not imply low popularity
Steam does not publish actual wishlist totals, so ggpick shows the observed rank and model confidence.
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