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FlameF0X
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FlameF0X
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FlameF0X/ChessSLM
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ChessSLM can play chess by generating moves sequentially in SAN notation.
It has been evaluated in matches against several language models, including:
The model achieves an averaging rating of around ~1054 Elo against other language models despite its small size.
| Model | Elo Rating |
|---|---|
| FlameF0X/ChessSLM | 1154 |
| DedeProGames/mini-chennus | 1114 |
| EleutherAI/pythia-70m-deduped | 1099 |
| nlpguy/smolchess-v2 | 1092 |
| DedeProGames/dialochess | 1078 |
| nlpguy/amdchess-v9 | 1073 |
| mlabonne/grandpythia-200k-70m | 1065 |
| FlameF0X/ChessSLM-PM | 1055 |
| DedeProGames/Chesser-248K-Mini | 1050 |
| bharathrajcl/chess_llama_68m | 1048 |
| FlameF0X/ChessSLM-RL | 1047 |
| distilbert/distilgpt2 | 1047 |
| Mattimax/EliaChess-70m | 1047 |
| HuggingFaceTB/SmolLM2-135M | 1042 |
| nlpguy/amdchess-v5 | 1041 |
| facebook/opt-125m | 1041 |
| EleutherAI/pythia-14m | 1037 |
| DedeProGames/chennus | 1034 |
| Smilyai-labs/Smily-ultra-1 | 1034 |
| huyvux3005/chessllm_FPT | 1034 |
Like many language-model-based chess systems, ChessSLM has several limitations:
These limitations are common for pure language-model chess agents that do not use external rule engines.
ChessSLM shows that very small language models can achieve meaningful chess performance when trained on domain-specific data.
It serves as a lightweight baseline for exploring LLM-based chess agents and specialized small language models (SLMs).