--- license: mit dataset_info: - config_name: challenge_100 features: - name: puzzle_id dtype: string - name: sudokupad_url dtype: string - name: author dtype: string - name: title dtype: string - name: rules dtype: string - name: initial_board dtype: string - name: solution dtype: string - name: rows dtype: int64 - name: cols dtype: int64 - name: visual_elements dtype: string - name: encoded_puzzle dtype: string splits: - name: test num_bytes: 442301 num_examples: 100 download_size: 233738 dataset_size: 442301 - config_name: ctc features: - name: youtube_id dtype: string - name: sequential_number dtype: int64 - name: date dtype: string - name: lgc_timestamp dtype: float64 - name: puzzle_id dtype: string - name: sudokupad_url dtype: string - name: author dtype: string - name: title dtype: string - name: rules dtype: string - name: initial_board dtype: string - name: solution dtype: string - name: rows dtype: int64 - name: cols dtype: int64 - name: visual_elements dtype: string - name: encoded_puzzle dtype: string splits: - name: test num_bytes: 18479173 num_examples: 2565 download_size: 6739069 dataset_size: 18479173 - config_name: nikoli_100 features: - name: puzzle_id dtype: string - name: sudokupad_url dtype: string - name: author dtype: string - name: title dtype: string - name: rules dtype: string - name: initial_board dtype: string - name: solution dtype: string - name: rows dtype: int64 - name: cols dtype: int64 - name: visual_elements dtype: string - name: encoded_puzzle dtype: string splits: - name: test num_bytes: 97444 num_examples: 100 download_size: 73883 dataset_size: 97444 configs: - config_name: challenge_100 data_files: - split: test path: challenge_100/test-* - config_name: ctc data_files: - split: test path: ctc/test-* - config_name: nikoli_100 data_files: - split: test path: nikoli_100/test-* ---

Sudoku-Bench

🤗 [Sudoku-CTC-Reasoning dataset]
🐙 [Sudoku-Bench GitHub]
📝 [Blog Post]

## Sudoku-Bench puzzle dataset The `SakanaAI/Sudoku-Bench` puzzle dataset contains three subsets: - `challenge_100`: A collection of 100 creative Sudoku puzzles. - `test` split: 100 puzzles - `nikoli_100`: A collection of 100 beautiful handmade standard Sudoku puzzles designed by Nikoli. - `test` split: 100 puzzles - `ctc`: A larger collection of puzzles featured as puzzles solves in the [Cracking the Cryptic](https://www.youtube.com/c/CrackingTheCryptic) (CTC) YouTube channel. - `test` split: 2565 puzzles ## Subset details ### `challenge_100` subset The purpose of the `challenge_100` subset is to evaluate the reasoning capabilities of LLMs on a diverse set of Sudokus. The subset includes - 15 4×4 puzzles (Sudoku variants) - 15 6×6 puzzles (Sudoku variants) - 50 9×9 puzzles (Sudoku variants) - 20 9×9 puzzles (standard Sudoku) taken from the `nikoli_100` set The selection of puzzles covers a range of difficulty. The 9×9 puzzles are roughly evenly distributed across difficulty levels 1 through 5 (using the [Logic Masters](https://logic-masters.de/Raetselportal/) difficulty scale). Around 5 puzzles are more difficult than the standard 5-star difficulty and are considered a challenge to the best human solvers. Difficulty is not a reflection of how complex the puzzle appears, and is not necessarily related to the length of the ruleset. Difficulty is a measure of how much skill and time is required for a human solver and is more closely a reflection of the depth of the idea required to find the puzzle's break-in. The 4×4 puzzles are significantly easier and most are rated 1-star difficulty. A subset of the 4×4 puzzles are quite simple and predominately test the model's ability to understand the constraints of Sudoku variant. Taken as a whole, the `challenge_100` includes a broad spectrum of difficulty and can be used to evaluate the performance of reasoning models of varying capabilities. ### `nikoli_100` subset The `nikoli_100` subset contains 100 beautiful handmade standard Sudoku puzzles designed by Nikoli, the Japanese puzzle company that popularized Sudoku. [Algorithimcally generated Sudoku puzzles](https://www.kaggle.com/datasets/rohanrao/sudoku) tend to find only puzzles of a certain type, namely whose solution path is similarly algorithmic. Human setters are more capable of creating puzzles that require deeper reasoning and creativity in the solve: see [this video](https://www.youtube.com/watch?v=mlLq8qaTLBo), for an example. ### `ctc` subset The `ctc` subset contains 2565 puzzles featured as puzzles solves in the Cracking the Cryptic channel. The `ctc` subset can be used in conjunction with the reasoning traces in [huggingface.co/datasets/SakanaAI/Sudoku-CTC-Reasoning](https://huggingface.co/datasets/SakanaAI/Sudoku-CTC-Reasoning). That is, you may wish to use the reasoning traces together with prompts derived from the content of the puzzle being solved, which the `ctc` subset can provide. ## Puzzle details Each puzzle in `SakanaAI/Sudoku-Bench` contains the fields: #### Puzzle data - `puzzle_id`: Identifier for the puzzle - `sudokupad_url`: Link to play the puzzle on [Sudokupad](https://sudokupad.app) - `author`: Creator of the puzzle - `title`: Name of the puzzle - `rules`: The puzzle rules - `initial_board`: String representation of the starting grid (empty cells shown as '.') - `solution`: String representation of the completed grid (81 digits for a 9×9 puzzle) - `rows`: Number of rows in the puzzle - `cols`: Number of columns in the puzzle - `visual_elements`: JSON-encoded string containing detailed specifications for visual components like circles, lines, and other custom markings specific to the puzzle variant (see [Sudoku-Bench/src/sudokupad_interaction/puzzle_tools](https://github.com/SakanaAI/Sudoku-Bench/blob/main/src/sudokupad_interaction/puzzle_tools.py) for the extraction of the visual elements) - `encoded_puzzle`: A compressed representation of the puzzle using SudokuPad's encoding scheme; for loading the puzzle directly in an offline SudokuPad (see [Sudoku-Bench/src/sudokupad_interaction/README.md](https://github.com/SakanaAI/Sudoku-Bench/blob/main/src/sudokupad_interaction/README.md)) The puzzles from the `ctc` subset contain additional fields: #### Video metadata - `youtube_id`: The YouTube ID of the video from which the puzzle was solved - `sequential_number`: The index of the puzzle in the video (for videos where multiple puzzles are solved; in most cases this is 1) - `date`: The upload date of the video - `lgc_timestamp`: The time in seconds when the phrase "let's get cracking" is said indicating the start of the solve in the video ## Example puzzle: Parity Fish Image The puzzle Parity Fish by Marty Sears is included in the `challenge_100` dataset. - `puzzle_id`: `'sxsm_MartySears_580c6fdbbba9bfb0e71ae19044f02d4c'` (using SudokuPad's internal `id` field) - `sudokupad_url`: `'https://sudokupad.app/wsj7iunsg6'` (link to the puzzle on SudokuPad) - `author`: `'Marty Sears'` - `title`: `'Parity Fish'` - `rules`: `'Normal sudoku rules apply; fill the grid with the digits 1-9 so that digits don\'t repeat in any row, column, and marked 3x3 box.\\nTwo cells adjacent along a red line must contain one even digit and one odd digit.\\nTwo cells connected by a white dot contain consecutive digits.\\nTwo cells connected by a black dot contain digits where one is double the other.',` - `initial_board`: `'.................................................................................'` (empty cells are represented as `.`) - `solution`: `'854369172976251834123478956419582367568937421237146598785694213691823745342715689'` - `rows`: `9` - `cols`: `9` ### Visual elements The `visual_elements` field is a JSON-encoded string containing detailed specifications for visual components of the puzzle. In the Parity Fish puzzle, there are 24 visual elements: 5 black dots, 16 white dots, and 3 red lines. You can display the visual elements using the `pretty_print_visual_elements` function in [`src/eval.utils`](https://github.com/SakanaAI/Sudoku-Bench/blob/main/src/eval/utils.py) in the [SakanaAI/Sudoku-Bench](https://github.com/SakanaAI/Sudoku-Bench) repo ```python import datasets import json from eval.utils import pretty_print_visual_elements puzzle = datasets.load_dataset("SakanaAI/Sudoku-Bench", "challenge_100")['test'][23] # Parity Fish puzzle print(pretty_print_visual_elements(json.loads(puzzle['visual_elements']))) # - shape: circle, color: white (stroke color: black), location: between r4c8 and r4c9 # - shape: circle, color: white (stroke color: black), location: between r5c8 and r5c9 # - shape: circle, color: white (stroke color: black), location: between r6c8 and r6c9 # - shape: circle, color: white (stroke color: black), location: between r5c1 and r5c2 # - shape: circle, color: white (stroke color: black), location: between r8c3 and r9c3 # - shape: circle, color: white (stroke color: black), location: between r7c1 and r8c1 # - shape: circle, color: white (stroke color: black), location: between r1c1 and r2c1 # - shape: circle, color: white (stroke color: black), location: between r7c7 and r7c8 # - shape: circle, color: white (stroke color: black), location: between r7c1 and r7c2 # - shape: circle, color: white (stroke color: black), location: between r9c8 and r9c9 # - shape: circle, color: white (stroke color: black), location: between r8c5 and r8c6 # - shape: circle, color: white (stroke color: black), location: between r1c4 and r2c4 # - shape: circle, color: white (stroke color: black), location: between r7c6 and r8c6 # - shape: circle, color: white (stroke color: black), location: between r2c7 and r3c7 # - shape: circle, color: white (stroke color: black), location: between r1c2 and r1c3 # - shape: circle, color: white (stroke color: black), location: between r1c5 and r2c5 # - shape: circle, color: black, location: between r3c2 and r4c2 # - shape: circle, color: black, location: between r4c7 and r4c8 # - shape: circle, color: black, location: between r2c3 and r3c3 # - shape: circle, color: black, location: between r9c2 and r9c3 # - shape: circle, color: black, location: between r8c8 and r9c8 # - line, color: red, coords: r3c2, r3c3, r3c4, r3c5, r3c6, r4c7, r5c8, r6c7, r7c6, r7c5, r7c4, r7c3, r7c2 # - line, color: red, coords: r4c1, r4c2, r5c3, r6c4, r7c4 # - line, color: red, coords: r6c1, r6c2, r5c3, r4c4, r3c5 ``` The intermediate `json.loads(puzzle['visual_elements']))` is a list of dictionaries, each of which is a verbose description extracted from the SudokuPad rendering engine. We encourage the user to adopt their own `pretty_print_visual_elements` function to display the visual elements in a way that is most useful for their application. Please see [`src/sudokupad_interaction/puzzle_tools`](https://github.com/SakanaAI/Sudoku-Bench/blob/main/src/sudokupad_interaction/puzzle_tools.py) for more details on the `visual_elements` field. ### Encoded puzzle The `encoded_puzzle` field is a byte64 encoding of the puzzle using SudokuPad's internal encoding method. The `encoded_puzzle` field can be used to obtain an alternate URL for the puzzle. Namely, `https://sudokupad.app/wsj7iunsg6` and [`https://sudokupad.app/{parity fish's encoded_puzzle string}`](https://sudokupad.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) will load the same puzzle. Both URLs point to Sven's SudokuPad website. However, only the second method works when running SudokuPad locally and avoids a call to the SudokuPad puzzle database. To ensure longevity of the benchmark, we provide a local usage in [`src/sudokupad_interaction`](https://github.com/SakanaAI/Sudoku-Bench/tree/main/src/sudokupad_interaction). The `encoded_puzzle` field can be ignored if using the text-only approach outlined in `src.eval` in this repo as all relevant information has already been extracted. ## Puzzle edge cases Because of the wide array of puzzles solved, the `ctc` subset is provided "as-is". There are a number of edge cases that make a pure text representation of the puzzle incomplete: 1. Some puzzles have visual elements that are difficult to encode in the `visual_elements` field (see below for a description of the `visual_elements` field). For example, the delightful [RatRun puzzles](https://www.youtube.com/watch?v=-KXjRMkYpA4) will not have a coherent textual description of the visual elements due to the visual complexity of the puzzle. 2. Other puzzles have the `solution` field omitted as many puzzle setters choose not to disclose the solution in SudokuPad. 3. A popular recent trend is the use of fog-of-war in Sudoku puzzles. For such puzzles, all hidden elements will be exposed in the `visual_elements` field meaning the puzzle will not be presented as intended by the puzzle setter. Please consider filtering the `ctc` subset based on your needs. ## Citation ```bibtex @misc{seely2025sudoku-bench, title={{Sudoku-Bench}}, author={Seely, Jeffrey and Imajuku, Yuki and Zhao, Tianyu and Cetin, Edoardo and Jones, Llion}, howpublished = {\url{https://github.com/SakanaAI/Sudoku-Bench}}, year={2025} } ```