Currently TCEC is in its season 27 and it is heading to its key moment, the Premier Division. There Stockfish, Leela Chess Zero, Berserk, KomodoDragon, and Seer will be joined by two ascending engines from the ongoing qualification, named League 1. There, after 23 rounds things are more surprising than ever! Seasoned fighters and medalists in TCEC events Rubichess, Rofchade, or Stoofvlees have practically no chance of joining the Premier Division. Rather, we will see Obsidian, Caissa, or Ceres enter the race for the first time.

Obsidian is currently the engine leading League 1, just past the halfway mark, with 15,5/23. The engine, written by 16 year old Gabriele Lombardo, is literally disrupting the field. While most pundits expected Ceres to win L1 and challenge the top positions in the TCEC Premier Division, it is the new version of Obsidian that shows what it takes to question the dominance of the top engines. It is now 0,5 points ahead of Caissa and a point ahead of Ceres. Only two of those engines will qualify for the Premier Division, but surely they will gun for medal positions and change a status quo in computer chess that we have seen for a decade.

Follow the TCEC championship live here

TCEC L1 standings

1. Obsidian 15,5/23
2. Caissa 15,0/23
3. Ceres 14,5/23
4. RubiChess 12,5/23
5. RofChade 11,0/23
6. Stoofvlees 10,5/23
7. Uralochka 10,5/23
8. Igel 10,0/23
9. PlentyChess 10,0/23
10. Viridithas 10,0/23
11. Revenge 9,5/23
12. Devre 9,0/23

See Obsidian in action now live at https://tcec-chess.com/

Obsidian is currently one of the top engines in the world. How did you decide to enter computer chess programming?

My interest in chess engines began about 2 years ago. I began playing chess with a friend OTB, and soon I found out about chess.com and began playing there. In chess.com the game review feature sparked my interest in chess engines because I was wondering, “How does this guy know what moves are good and bad?”. So I found out about chess engines and I worked for some months on a kind of “toy” engine. Then, I decided to rewrite everything from scratch in a more serious manner and that was what is now Obsidian.

The other day in chat someone mentioned that you are very young, actually the youngest of all developers in TCEC

That’s right. Every engine developer I have ever talked to is older than me. I am 16 years old and will turn 17 in March 2025.

The new season of Top Chess Engine Championship TCEC has started with Swiss 7, the strongest chess event regarding playing strength. What are your expectations?

Obsidian most recent versions defeated Komodo Dragon 3.3 (the latest version) on SP-CC and Ipmanchess (two leaderboards). I hope Obsidian can repeat this performance in the Top Chess Engine Championship. The number of games played on TCEC is limited, so bad luck could happen. Hopefully not!

What do you consider the biggest strength of Obsidian? And the biggest weakness?

The biggest strength of Obsidian is the evaluation. It is not a random Leela data NNUE – my NNUE is, by a big margin, stronger than the NNUE of any other Leela data engine, outside of Stockfish of course. Excluding the datagen process (which is missing), there is a lot of effort into training. It was speculated about 2 months ago by a Torch developer that Obsidian’s evaluation might be almost as strong as that of Torch.

The biggest weakness is probably the search algorithm, being the engine very fast in terms of nps.

What are the original inventions in Obsidian?

I don’t know if calling them “inventions” is appropriate. There are several original implementation details that gained Elo in my engine in comparison to the way I’ve seen other engines do things. They are very technical and specific things I won’t go over.

Regarding speed, Obsidian until recently had 2 completely original techniques about efficient updates of the neural network. Recently I had to remove them due to their high RAM consumption – but they were significant speedups.

Lastly, I don’t do datagen, but in the training process itself I use various techniques that result in a (far) stronger evaluation than that of engines with similar training data.

What are the things that you are currently researching?

In this period I am trying to introduce 3 hidden layers (instead of 1) in the neural network evaluation of Obsidian. Every attempt until now has been a failure. I can successfully measure an increased strength of evaluation, but the speed loss is exaggerate.

Does Obsidian have plans to pull away from using Leela data for NNUE towards a more original approach?

Generating data by myself would be impossible for now, due to my very restricted amount of resources/hardware. I don’t think I could find someone else who would dedicate to generate data for Obsidian either.

Make a prediction for top 5 in the current TCEC Swiss 7

My prediction is: Stockfish, LCZero, Ceres, Berserk, Obsidian

Do you follow human chess games? Are you going to follow the Chess Olympiad in Budapest?

I watch human games sometimes. I mostly follow Hikaru, and last week I’ve been watching the Speed Chess Championship. I didn’t know about the chess Olympiad in Budapest until I read your message – I will probably watch some games.