Gomocup Schedule, 5th-7th of June 2026
There will be 2 freestyle (20x20) groups (i.e., Freestyle-20 1 and 2), 2 freestyle (15x15) groups (i.e., Freestyle-15 1 and 2), 1 fastgame group (Fastgame), 2 standard groups (i.e., Standard 1 and 2), 1 renju group (Renju), and 1 caro group (Caro) in Gomocup 2026. Elo rating system is used to evaluate AIs' strength. The memory limit is determined to 1GB. Time per move/per match will be 5s/120s for fastgame, 300s/1000s for final leagues (i.e., Freestyle-20 1, Freestyle-15 1, Standard 1, Renju, and Caro), and 30s/180s for the rest (i.e., Freestyle-20 2, Freestyle-15 2, and Standard 2).
AIs were divided into different freestyle and standard groups according to the placement in the last tournament. For Freestyle-20 2, Freestyle-15 2, and Standard 2, the top 4 AIs will move up to the next group (i.e., Freestyle-20 1, Freestyle-15 1, and Standard 1, respectively). If the top k (k>4) places were all taken by new or updated AIs in a group, then all these k AIs would advance to the next group.
In Fastgame, Freestyle-20 2, Freestyle-15 2, and Standard 2, we do not match every pair of AIs. Instead, for old AIs, we only match every pair of them whose last year's Elo difference was no more than 400. We still match each brand new/updated AI with all AIs.
The unlimited tournament, which has no hardware constraints, will not be held this year, as we received no valid submissions for this league this year.
Schedule (tentative)
- Standard 2 - Saturday 05:30 AM (GMT)
- Freestyle-20 2 - Saturday 07:50 AM (GMT)
- Freestyle-15 2 - Saturday 08:20 AM (GMT)
- Fastgame - Saturday 14:00 AM (GMT)
- Renju - Sunday 00:20 AM (GMT)
- Freestyle-20 1 - Sunday 01:50 AM (GMT)
- Standard 1 - Sunday 03:40 AM (GMT)
- Freestyle-15 1 - Sunday 11:30 AM (GMT)
- Caro - Monday 12:20 PM (GMT)
What is new?
Updates
- AlphaGomoku (Kozarzewski) - Bugfixes and tuning.
- ANGEL - Starting from this version, an AlphaGo Zero-like algorithm is adopted, replicating the four optimization points from Chapter 3 of the KataGo paper.
- DDQK-Conquer - DDQK-Conquer has greatly improved the computing speed, effectively combining C++ and Python, so that the space and speed can be improved and optimized more effectively. It is no longer limited to the traditional alpha-beta pruning algorithm, but further adopts an algorithm similar to NNUE.
- Embryo - Refactored quiescence search, better move ordering.
- Figrid - α-β engine with NNUE evaluation (via the noru Rust library). Standard search techniques (IID, aspiration, IIR, LMR, TT, qsearch) plus a Pattern4-mini threat cache and continuation history driving move ordering. NNUE evaluation via the noru library. Adds phase-based time management.
- Kanec - Based on proof numbers. Some improvements to mitigate the drawbacks of this method.
- Katagomo - The 2026 version is approximately 200 Elo stronger than the 2021 version across all rule sets. In addition, the Caro rule is now supported.
New AI
- Chloris - developed by Nelly Semenova from Russia. Tournament engine for Standard-15 Gomoku with a custom NNUE evaluation trained for Standard 15x15 play on approximately 3 million positions, iterative-deepening alpha-beta search, and a dedicated tactical layer, including tactical predicates, forcing-move checks, and urgent-threat defense. The combined positional evaluation was tuned through games against stronger engines.
- Mintaka - developed by JeongHyeon Choi from South Korea. Renju engine written in Rust, currently under development, based on PVS and (temporary) heuristic algorithm.
- Monas - developed by Guanwu Liu from China. Monas employs a pre-computed pattern matching table for fast threat recognition, combined with Alpha-Beta search; a fallback mechanism is invoked when needed to ensure stable move generation.
- Olechka - developed by Dima Suraev from Russia. alpha-Beta pruning search with Transposition Table, Zobrist Hashing, Iterative Deepening and partial depth caching. Custom bitwise evaluation optimized for Freestyle rules. Secret heuristics.
- SkyZero - developed by Sky Cheng from China. SkyZero is a Gomoku AI powered by the Gumbel AlphaZero algorithm.
- Starpoint - developed by You Huang from China. Starpoint is a Gomoku engine based on Monte Carlo Tree Search and transformer-based evaluation, with Proof-Number Search used for VCT search inside the engine.
- TKGomoku - developed by Tae Kim from USA. It uses iterative deepening alpha-beta/PVS-style negamax search, transposition table, threat-aware move ordering, immediate tactical detection, VCF/VCT-style probes, handcrafted line/pattern evaluation, and lightweight NNUE/policy/opening-book files.
- VibeFive - developed by Lu-Chuan Liu from China. VibeFive is a C++ program based on alpha-beta pruning search and a traditional evaluation table. Its development process combines automated AI programming with manual modifications. An LLM agent loop is used for algorithm iteration and parameter tuning. The LLM involved in the development include, but are not limited to, GPT-5.5, Claude opus 4.7, and GLM-5.1.
Tournament Computers
Tencent Cloud Servers SA9.8XLARGE64 (Windows Server 2025 Datacenter, x64 32 vCPU (AMD EPYC 9K65), 64GB RAM)