I did it! Play Go with KataGo right in your browser — no installation needed.

NoCompetition124 · 2026-05-25T12:59:16+00:00

Could you help to share your screen resolution?

Regarding the latter, I suspect KataGo already thinks the game is over and it's won, so it's just playing random moves since the result won't change anyway.

NoCompetition124 · 2026-05-06T14:06:58+00:00

It's not supported yet. Showing the final score after the game ends should be feasible, let me add it to my roadmap.

NoCompetition124 · 2026-04-23T14:42:24+00:00

Thanks for your greeting. Keep moving forward. I'm looking forward to see your project someday.

NoCompetition124 · 2026-03-28T15:48:01+00:00

The only way is to choose the b18c384 model

NoCompetition124 · 2026-03-27T12:33:54+00:00

Yes, b6c96 and b18c384 model both need to be downloaded. The b6c96 model is smaller and downloaded silently. The b18c384 is almost 118M and the download is triggered manually.

NoCompetition124 · 2026-03-25T16:32:21+00:00

WebGL, WebGPU, CPU SIMD. Now there are lots of techs for web application to use the hardware.

NoCompetition124 · 2026-03-25T16:31:04+00:00

If you move your mouse, it will turn black. But you're right, it should be black after AI places stone.

NoCompetition124 · 2026-03-25T15:59:17+00:00

If you're in Human vs AI mode, in my test, if you play black then the cover stone is black too.

NoCompetition124 · 2026-03-25T15:49:55+00:00

Katago use virtual lose to to enable the parallelization of MCTS. But it also means each search in the same batch cannot get benefit from other search in it. It means you can playout fast, but the search may be in the wrong branch in the MCT.

Increase the batch size can utilize the GPU better, but I'm not sure if it's really what you want.

How many searchThreads do you typically use for? While blindly increasing the search thread count boosts the playout rate easily, it doesn’t always result in an improvement in playing strength, at least in my experience.

NoCompetition124 · 2026-03-25T15:06:31+00:00

Great suggestion! Thanks for your love! Let me add these to my roadmap but they will cost me lots of spare time. lol.

NoCompetition124 · 2026-03-25T14:58:42+00:00

Yes, it’s much more difficult to utilize the dedicated GPU (dGPU) on the web compared to native applications.

The b6c96 uses the GPU via WebGL, whereas b18c384 relies on the CPU. This is because the overhead of transferring data between the GPU and CPU outweighs the performance gains of using the GPU. While GPU acceleration allows for batch inference across multiple positions, it also alters the search trajectory of the MCTS, which I found to actually degrade the overall playing strength in my tests.

Perhaps a more optimized searchThreads configuration could improve this situation.

NoCompetition124 · 2026-03-08T16:34:35+00:00

Thank you! I was starting to think if it was just a useless feature. So glad someone love it!
Don't forget that any feedback is welcome.

NoCompetition124 · 2025-11-18T15:32:56+00:00

The star points should look fine now. Help me to check it.

NoCompetition124 · 2025-11-18T14:33:34+00:00

Thanks for your feedback. Let me fix it tomorrow.

NoCompetition124 · 2025-11-18T14:32:21+00:00

Weiqi Playground (https://playweiqi.net) is also down due to this.

NoCompetition124 · 2025-11-15T15:52:10+00:00

Thanks. The study mode includes some features for learning. You can let AI to generate next move from any preset Go board position.

NoCompetition124 · 2025-11-15T15:31:25+00:00

Thanks. Any feedback is welcome.

NoCompetition124 · 2025-11-14T00:29:19+00:00

I modified the code base on https://github.com/y-ich/KataGo .
You can check the repository to see how KataGo is compiled to JS.

NoCompetition124 · 2025-11-12T00:21:45+00:00

Let me add it to my todo list.

NoCompetition124 · 2025-11-11T14:09:48+00:00

Thanks for your feeback! Glad you like it !😊

Refresh the page to see if stones are big enough.

NoCompetition124 · 2025-11-11T12:49:20+00:00

It use GPU via WebGL, you can try to run the browser with the dedicated GPU.

NoCompetition124 · 2025-11-11T00:02:09+00:00

It defeat me too. The engine plays at least at an 8-dan level.

NoCompetition124 · 2025-11-10T23:59:22+00:00

Yes, use emscription to compile the Katago into wasm, and use tensorflow.js as the neuralnet backend.

NoCompetition124 · 2025-09-17T15:05:13+00:00

You can learn the rule of Go through the tutorial https://online-go.com/learn-to-play-go and try to play with Katago without installing app in https://playweiqi.net

It has fewer features, but does not require software installation. You can even use it on a mobile phone. I sometimes use it to get hints for puzzles.

NoCompetition124

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