Games and long tasks
We track 68 benchmarks in games and long tasks. They run from everyday level to research frontier level.
OpenAI held the top games and long tasks score 46% of the contested time
That's about 21 of the 46 months since January 2023, averaged over the benchmarks below. The easiest benchmarks are at the top. Versions of one test share a row, with a dark tick at each new version. We stop the clock, and fade the rest of the row, when the best score passes 85%, or at the newest score if 45 days go by without another.
OpenAI ByteDance Seed xAI Anthropic Google DeepMind DeepSeek Moonshot AI
Everyday Most adults, without training
Competition The strongest students, in olympiad-style contests
Expert Specialists with years of training, often over hours of work
Share of contested time at number one
OpenAI 46% 
Google DeepMind 19% Anthropic 18% xAI 14% 
DeepSeek 2%
Google DeepMind 19% Anthropic 18% xAI 14% DeepSeek 2% Scores come from each benchmark’s own leaderboard, from Epoch AI’s runs and from labs’ reports on their own models. We date Epoch runs by the model’s release and lab reports by when they came out. Labs pick their own settings, so a lab’s claim can beat an independent run of the same model. Turn off lab claims to see independent runs only.
OpenAI xAI Anthropic Google DeepMind DeepSeek Moonshot AI
Everyday Most adults, without training
Competition The strongest students, in olympiad-style contests
Expert Specialists with years of training, often over hours of work
Share of contested time at number one, independent runs only
OpenAI 48% Anthropic 18% Google DeepMind 16% xAI 15% DeepSeek 2%
Google DeepMind 16% xAI 15% DeepSeek 2% Only each benchmark’s own leaderboard and Epoch AI’s runs, dated by the model’s release. We leave out benchmarks that only labs report.
From everyday to research frontier level
Grouped by who could solve the tasks, from things most adults can do to open research problems. The bar under each name is its best score.
Everyday
Most adults, without training
- SnakeBench
- LisanBench
- LLM Chess
- Step Race
- Elimination Game
- BALROG
- Game Arena Checkers
- Game Arena Dark Hex
- Game Arena Four in a Row
- Game Arena Dots and Boxes
- Game Arena Bargaining
- Game Arena Clobber
- Game Arena Lines of Action
- Game Arena Nine Men's Morris
- Game Arena Reversi
- Game Arena Ultimate Tic-Tac-Toe
- Game Arena Word Association
- Game Arena Coin Game
- Game Arena Word Art
- ARC-AGI-3
- EBR-bench
- PACT
- Game Arena Five in a Row
- BalatroBench
- GameWorld
- CUA-bench
- SpireClimb StS2 A10
- MineDojo
- Orak
- UI-TARS 15 Games Collection
- TextQuests
- AdaExploreBench
- AI Diplomacy
- Cooperate to Compete (C2C)
- DiG-bench
- GameHorizon
- Gym-Anything-RT
- Learn2Play Bench
- LLM Colosseum
- lmgame-Bench
- SnorkelWordle
- SpeedrunBench
Expert
Specialists with years of training, often over hours of work
- Pencil Puzzle Bench
- Game Arena Chess
- Kaggle Game Arena
- Game Arena Go
- Game Arena Poker
- CEO-Bench
- CivBench
- Agent Poker Bench
- Time Horizon Index: KSP
- WitnessBench
- Game Arena Chess Openings
- StarSkirmish Bench
- Game Arena Werewolf
- SpireClimb
- SpireClimb StS1 A20 Heart
- Brood War Bench
- Factorio Learning Environment
- VideoGameBench
- Swarm Bench
- BabaIsBench
- OdysseyArena
- PokeAgent Challenge
Research frontier
Researchers, on open problems or tasks that take days
Another 1 has no level. Levels don’t apply to arenas, safety evaluations or composite indices.
By kind
Puzzles and chess
| Benchmark | Level | Scored | Best score | Status |
|---|---|---|---|---|
| LisanBench Models build the longest chain of distinct English words from a given start word, each differing from the last by one letter. The score sums valid chain lengths over all start words. | Everyday | Checked automatically |  37152.2 | Not in cards |
| LLM Chess Models play chess in multi-turn dialogs against a random player or the Komodo Dragon engine. The board reports wins, Elo and game duration, which tracks instruction following. | Everyday | Ranked by matches | 1,614 | Not in cards |
| Chess Puzzles Models find the single best next move in 100 chess puzzles that Epoch generated with a chess engine. Scored by the share solved. | Competition | Checked automatically | 76% | Not in cards |
| Mystery Game Puzzles 100 mid-game positions from an undisclosed puzzle variant of a well-known game. Model picks the single best move, checked against an answer key. | Competition | Checked automatically | 84% | Not in cards |
| Pencil Puzzle Bench Models solve 300 pencil puzzles of 20 varieties with unique solutions, either in one shot or agentically with step checks. Every board state can be verified against the rules. | Expert | Checked automatically | 97.6% | Not in cards |
| Game Arena Chess Language models play full chess games against each other with the board given as FEN and PGN text. Ratings come from many games between each pair. | Expert | Ranked by matches | 1,453 | Not in cards |
| Game Arena Checkers Language models play American checkers against each other, with forced jumps and crowned kings. Ratings come from head-to-head games. | Everyday | Ranked by matches | 1,338 | Not in cards |
| Game Arena Dark Hex Language models play Hex without seeing the opponent's stones, so they must probe cells to learn the hidden board while building a path. | Everyday | Ranked by matches | 612 | Not in cards |
| Game Arena Four in a Row Language models play a Connect Four style game and try to line up four of their tokens before the opponent does. | Everyday | Ranked by matches | 923 | Not in cards |
| Game Arena Dots and Boxes Language models take turns drawing lines between dots on a grid. Closing the fourth side of a box claims it. | Everyday | Ranked by matches | 1,219 | Not in cards |
| Game Arena Clobber Language models play Clobber, where every move captures an adjacent enemy stone. The player who makes the last legal move wins. | Everyday | Ranked by matches | 847 | Not in cards |
| Game Arena Go Language models play Go against each other through the Game Arena text harness. Ratings come from head-to-head games. | Expert | Ranked by matches | 1,762 | Not in cards |
| Game Arena Lines of Action Language models play Lines of Action, where a piece moves as far as the number of pieces on its line. The goal is to join all of one's pieces into one group. | Everyday | Ranked by matches | 1,185 | Not in cards |
| Game Arena Nine Men's Morris Language models play Nine Men's Morris. Forming a row of three, called a mill, lets a player remove one of the opponent's pieces. | Everyday | Ranked by matches | 1,022 | Not in cards |
| Game Arena Reversi Language models play Reversi, also called Othello, flipping the opponent's disks that they flank in a line. | Everyday | Ranked by matches | 1,102 | Not in cards |
| Game Arena Ultimate Tic-Tac-Toe Language models play nine linked tic-tac-toe boards. Each move decides which small board the opponent must play next. | Everyday | Ranked by matches | 608 | Not in cards |
| ARC-AGI-3 Interactive game environments where agents must explore, infer goals and rules, and act efficiently without instructions. | Everyday | Checked automatically | 100% | In use |
| EBR-bench Agent plays the board game Earthborne Rangers 10-30 times in a row. Scored on objectives completed (of 21) to test learning from experience. | Everyday | Checked automatically | 78.1% | Not in cards |
| Game Arena Five in a Row Language models play a gomoku-style game and try to line up five of their tokens before the opponent does. | Everyday | Ranked by matches | 1,131 | Not in cards |
| WitnessBench Agents play unseen line-puzzle games in the style of The Witness without being told the rules. They must discover rules by experiment and apply them to harder levels. | Expert | Checked automatically | 46.5% | Not in cards |
| Game Arena Chess Openings Language models play chess against each other from varied two-move openings sampled from 20 popular human openings. The board is given as text. | Expert | Ranked by matches | 1,263 | Not in cards |
| AdaExploreBench Language model agents explore environments with hidden rules, infer the rules from evidence and adapt when the rules change without notice. | Everyday | Checked automatically | Not in cards | |
| BabaIsBench Agents play levels of the puzzle game Baba Is You through a text interface and win by rewriting the rules. Models are compared on pass rate, speed and cost. | Expert | Checked automatically | Not in cards | |
| DiG-bench Agents play text-only games whose transformation rules and win conditions are hidden, so they must discover the rules by experimenting. Every game was beaten by at least one human on a first attempt. | Everyday | Checked automatically | Not in cards | |
| Learn2Play Bench Agents play unfamiliar games whose rules are not given and must learn from experience across episodes. Improvement over repeated play is the measure. | Everyday | Checked automatically | Not in cards | |
| OdysseyArena Agents explore interactive environments built from four transition primitives and must work out the hidden dynamics over long horizons. OdysseyArena-Lite has 120 standard tasks. | Expert | Checked automatically | Not in cards | |
| SnorkelWordle Models play Wordle on 100 rare five-letter English words, with six guesses and letter feedback after each guess. The score is the win rate. | Everyday | Checked automatically | Not in cards |
Video games
| Benchmark | Level | Scored | Best score | Status |
|---|---|---|---|---|
| BALROG Agentic reasoning on games (NetHack, Crafter, BabyAI, MiniHack...) for LLMs and VLMs. | Everyday | Checked automatically | 68.3% | Not in cards |
| CivBench Models play full games of Civilization V with the Vox Populi mod against each other on matched maps and seeds. Pairwise skill ratings rank long-term strategy. | Expert | Ranked by matches | 1,634 | Not in cards |
| BalatroBench Models play the deck-building roguelike Balatro through an API bot. The leaderboard compares how far each model and strategy gets in a run. | Everyday | Checked automatically | 19.3 | Not in cards |
| GameWorld Multimodal game agents play 34 browser games across 170 tasks. Outcomes are checked from the game state. | Everyday | Checked automatically | 41.9% | System cards only |
| Time Horizon Index: KSP Agents get five days to build and run a space program in Kerbal Space Program. The score is progress through 30 fixed missions. | Expert | Checked automatically | 91.3% | Not in cards |
| CUA-bench Computer-use agents play six commercial video games, such as Minecraft, SUPERHOT and eFootball, using only a keyboard and mouse. Half of the games are held out. | Everyday | Checked automatically | 19.2% | Not in cards |
| StarSkirmish Bench Each model gets one hour in its lab's own CLI to write a StarCraft: Brood War bot in C++. The score is its win rate against human-written bots. | Expert | Ranked by matches | 57.3% | Not in cards |
| SpireClimb Agents play Slay the Spire 1 and 2 at max difficulty through a computer-use harness on fixed seeds. Score is the mean win rate. | Expert | Checked automatically | 25.7% | Not in cards |
| SpireClimb StS1 A20 Heart Agents play Slay the Spire 1 through its graphical interface at Ascension 20 and must defeat the Heart. Scored by win rate over fixed seeds. | Expert | Checked automatically | 20% | Not in cards |
| SpireClimb StS2 A10 Agents play Slay the Spire 2 at Ascension 10 through screenshots and mouse and keyboard, 15 runs per character. Scoring is the win rate. | Everyday | Checked automatically | 34.7% | Not in cards |
| Brood War Bench Coding agents play StarCraft: Brood War against each other in real time. Systems are ranked by win rate over matches, with cost per game. | Expert | Ranked by matches | 100% | Not in cards |
| Factorio Learning Environment Agents write Python programs that control a Factorio factory, in lab tasks with fixed resources and in open play. Scored by production throughput, milestones and lab task success. | Expert | Checked automatically | 293206.0 | Not in cards |
| VideoGameBench Vision-language models play 10 popular 1990s Game Boy and MS-DOS games in real time from raw frames. Scored by the share of each game completed. | Expert | Checked automatically | 0.48% | Not in cards |
| MineDojo Agents complete open-ended tasks in Minecraft, such as mining blocks and fighting mobs, from a large simulation suite. Programmatic checks score many tasks. | Everyday | Checked automatically |  49% | Fading |
| Orak LLM agents play 12 popular video games across most genres through an MCP interface. Scores come from in-game progress or outcomes per title. | Everyday | Checked automatically |  22.9 | Fading |
| UI-TARS 15 Games Collection GUI agents play 15 browser games such as 2048, Infinity-Loop and Snake-solver from screenshots. Each game score is divided by a human score, and the mean is reported. | Everyday | Settled by events | 59.8 | Dropped |
| TextQuests Agents play 25 classic interactive fiction games. Measures game progress and harmful actions per 100 steps. | Everyday | Checked automatically | 2.40 | System cards only |
| GameHorizon Models are tested on gameplay over several time horizons. Tasks combine visual understanding, instruction decomposition, planning and precise action control, using offline data instead of noisy rollouts. | Everyday | Checked automatically | Not in cards | |
| Gym-Anything-RT Vision-language agents play 100 real-time browser minigames by screenshots and mouse and keyboard input. Each game also has a paused, non-real-time counterpart, so the gap shows the cost of acting in real time. | Everyday | Checked automatically | Not in cards | |
| LLM Colosseum Two models each control a fighter in Street Fighter III and choose moves from text descriptions of the game. Wins give Elo ratings. | Everyday | Ranked by matches | Not in cards | |
| lmgame-Bench Models play platformer, puzzle and narrative games such as Sokoban, Tetris, 2048 and Candy Crush through a Gym-style API with perception and memory scaffolds. | Everyday | Settled by events | Not in cards | |
| PokeAgent Challenge Agents compete in Pokemon battles under partial observability in a Battling Track and play the Pokemon RPG in a Speedrunning Track that needs long-horizon planning. | Expert | Ranked by matches | Not in cards | |
| SpeedrunBench Agents try to finish goals in 10 video games as fast as possible. Score is time to goal in frames or seconds, lower is better. | Everyday | Checked automatically | Not in cards |
Multi-agent games
| Benchmark | Level | Scored | Best score | Status |
|---|---|---|---|---|
| SnakeBench Two language models each steer a snake on a shared board in a turn-based game, and the one that survives longest wins. Ratings come from many head-to-head games. | Everyday | Ranked by matches | 38 | Not in cards |
| Step Race Several models talk in public, then secretly pick moves in a race where colliding moves cancel. The game tests cooperation and deception. | Everyday | Ranked by matches | 5 | Not in cards |
| Elimination Game Models play a multi-player game of public and private talk, alliances and votes to eliminate each other. A jury of eliminated players picks the winner. | Everyday | Ranked by matches | 8 | Not in cards |
| Kaggle Game Arena Language models play each other in board, card and word games through a text harness. One leaderboard ranks models across all Game Arena games. | Expert | Ranked by matches | 535 | Not in cards |
| Game Arena Bargaining Two language models negotiate how to split a pool of items, each with private item values. Each side tries to reach a good deal without giving away its values. | Everyday | Ranked by matches | 277 | Not in cards |
| Game Arena Word Association Teams of language models give one-word clues and guess linked words, in a game like Codenames, against an opposing team. | Everyday | Ranked by matches | 596 | Not in cards |
| Game Arena Coin Game Two language models move on a grid and pick up coins. Each should collect the coins that score for it and avoid the rest. | Everyday | Ranked by matches | 514 | Not in cards |
| Game Arena Word Art Language models take turns drawing a word as ASCII art and guessing what the other model drew. | Everyday | Ranked by matches | 2,473 | Not in cards |
| Game Arena Poker Language models play heads-up no-limit Texas Hold'em against each other. Models are ranked by mean big blinds won per 100 hands. | Expert | Ranked by matches | 30.3 | Not in cards |
| PACT Two models bargain over 20 rounds as buyer and seller, each with a hidden private value. Matches across many pairings rank the models. | Everyday | Ranked by matches | 1,607 | Not in cards |
| CEO-Bench Agents steer a simulated AI startup for 500 days, gathering noisy information and adapting plans. The outcome of the simulated company is the score. | Expert | Settled by events | $22,148,357 | Not in cards |
| Agent Poker Bench Models play 10-seat no-limit Texas Hold'em tournaments against each other. Chip counts and elimination order feed TrueSkill ratings. | Expert | Ranked by matches | 1,132 | Not in cards |
| Game Arena Werewolf Teams of language models play the social deduction game Werewolf in natural language. Villagers must find the hidden werewolves, who try to deceive them. | Expert | Ranked by matches | 0 | Not in cards |
| Swarm Bench Models orchestrate agent swarms on complex tasks that benefit from coordinated decomposition and parallel execution. | Expert | Checked automatically | 76.3% | System cards only |
| AI Diplomacy Models play the board game Diplomacy against each other, one power each. They negotiate, form alliances and betray each other in written messages. | Everyday | Ranked by matches | Not in cards | |
| Anthropic large agent teams tasks Internal 24-hour tasks for teams of 1-100 agents: build a company knowledge base, or formalize a theorem in Lean. | Research frontier | Checked automatically | System cards only | |
| Cooperate to Compete (C2C) Multi-player conquest game with private non-binding negotiation and secret asymmetric objectives. LM agents scored by win rate against humans and other agents. | Everyday | Ranked by matches | Not in cards | |
| TextArena Collection of competitive text games for LLM eval and RL, with an online Elo leaderboard. | Ranked by matches | Not in cards |