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Life & fun · alternatives · 2026

PB

24 alternatives to Pac-Bench – How well can models one-shot a Pac-Man game?

Pac-Man bench: how well a model and harness can recreate Pac-Man from a single prompt.

Pac-Bench is a benchmark that measures how well AI models can recreate a working Pac-Man game from a single prompt. It tests both the model's capabilities and the quality of the system prompt or "harness" used to guide… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes.

  1. 1

    Six AI decision models played Pac-Man in real time against the classic arcade ghosts. See the leaderboard, watch their games, or play against them.

    16d ago · opper.ai · its alternatives →

  2. 2
    Meshy-1▲611

    Create stunning 3D models with AI

    2023 · meshy.ai · its alternatives →

  3. 3EF

    I’ve been building Echo (https://echo.tracerml.ai/), an experiment in making one AI system out of a pool of open-weight models rather than choosing a single model and using it for every task. It started with a simple experiment. I took a group of models, including GLM-5.2, Kimi K2.7 and others, and ran them on the same evaluations. Then I measured what would happen if, for each problem, you somehow knew in advance which models would be useful and how their outputs should be combined. That hypothetical system performed substantially better than any individual model in the pool.…

    Jul 2026 · its alternatives →

  4. 4

    After training calculator agent via RL, I really wanted to go bigger! So I built RL infrastructure for training long-horizon terminal/coding agents that scales from 2x A100s to 32x H100s (~$1M worth of compute!) Without any training, my 32B agent hit #19 on Terminal-Bench leaderboard, beating Stanford's Terminus-Qwen3-235B-A22! With training... well, too expensive, but I bet the results would be good! *What I did*: - Created a Claude Code-inspired agent (system msg + tools) - Built Docker-isolated GRPO training where each rollout gets its own container - Developed a multi-agent…

    2025 · github.com · its alternatives →

  5. 5

    Animate your static 3D models with AI

    2023 · app.anything.world · its alternatives →

  6. 6

    The biggest Pac-Man game in the world

    2017 · google.com · its alternatives →

  7. 7IB

    We wanted to do something very challenging to prove to ourselves that we can do anything we put our mind to. The reasoning for why we chose to build a toy TPU specifically is fairly simple: - Building a chip for ML workloads seemed cool - There was no well-documented open source repo for an ML accelerator that performed both inference and training None of us have real professional experience in hardware design, which, in a way, made the TPU even more appealing since we weren't able to estimate exactly how difficult it would be. As we worked on the initial stages of this project, we…

    2025 · tinytpu.com · its alternatives →

  8. 8PA
  9. 9
    Bullet▲240

    Hi HN, excited to be sharing this with you guys today. TL;DR: Bullet is a fast coding agent. At our company, we were burning hours waiting on agent runs. The models weren’t the problem. The agent loops around them were slow (unnecessary planning, oversized context, repeated searches, and serial tool calls). So we built Bullet as a passion project, the goal being to help you iterate faster, without giving up quality: - It automatically selects the model and reasoning level for each prompt. - It runs independent searches, reads, and commands in parallel. - It uses targeted code search instead…

    Aug 2026 · codewithbullet.com · its alternatives →

  10. 10

    LLM-generated real-time commentary for Pong. Contribute to pncnmnp/xpong development by creating an account on GitHub.

    2025 · github.com · its alternatives →

  11. 11

    We built a computer use agent once and got it benchmarked at the 2nd position in the biggest benchmark for this field but in the process, we realized one thing, how outdated and inefficient these benchmarks are and how they don't truly capture how these tasks went. So we thought a community led benchmarking arena would be the way to go about. https://coarena.ai/. You just have to put in a task and two side by side windows with hidden models will show up and do the same task and at the end you vote which one did better(or none). We have a leaderboard where we rank all the…

    Aug 2026 · coarena.ai · its alternatives →

  12. 12RP

    Keep one eye on the first ghost and the other on the second

    2025 · reverse-pacman.staticrun.app · its alternatives →

  13. 13
    Web Bench▲138

    A 10x better benchmark for AI browser agents

    2025 · webbench.ai · its alternatives →

  14. 14

    The Emotion Engine has 32 MB of RAM total, so the trick is streaming weights from CD-ROM one matrix at a time during the forward pass — only activations, KV cache and embeddings live in RAM. This means models bigger than the RAM can still run, they just read more from disc. Had to build a custom quantized format (PSNT), hack endianness, write a tokenizer pipeline, and most of the PS2 SDK from scratch (releasing that separately). The model itself is also custom — a 10M param Llama-style architecture I trained specifically for this. And it works. On real hardware.

    Mar 2026 · github.com · its alternatives →

  15. 15
    cto bench▲125

    The ground truth code agent benchmark

    Dec 2025 · cto.new · its alternatives →

  16. 16

    I built this because I couldn't find honest numbers on how well VLA models [1] actually work on commercial tasks. I come from search ranking at Google where you measure everything, and in robotics nobody seemed to know. PhAIL runs four models (OpenPI/pi0.5, GR00T, ACT, SmolVLA) on bin-to-bin order picking – one of the most common warehouse operations. Same robot (Franka FR3), same objects, hundreds of blind runs. The operator doesn't know which model is running. Best model: 64 UPH. Human teleoperating the same robot: 330. Human by hand: 1,300+. Everything is public – every run with…

    Mar 2026 · phail.ai · its alternatives →

  17. 17

    Delight your terminal with paclear, a whimsical take on the 'clear' command accompanied by a PAC-MAN animation. It's a fun way to clear your terminal screen and enjoy a bit of nostalgia at the same time.

    2023 · github.com · its alternatives →

  18. 18

    Sprig is a tile based game engine made by Hack Club that's like Scratch's older brother but has it's own set of unique limitations. All sprites need to be made in Bitmap and uses a midi like event sequencer to get any music into it, since it's meant for a different set of hardware, you can only use very basic controls too. I made a version of PacMan inside it that has randomly generated mazes every time and mostly works well!

    2025 · sprig.hackclub.com · its alternatives →

  19. 19

    A final project for Advanced Machine Learning. Build bots to play against this Tetris Sandbox! - mbrenman/TetrisPlayground

    2015 · github.com · its alternatives →

  20. 20
    Ponzu▲89

    AI-powered textures for 3D models

    2022 · its alternatives →

  21. 21ΤB

    τ-Bench is an open benchmark for evaluating AI agents on grounded, multi-turn customer service tasks with verifiable outcomes. It's been great to see the community adopt it since launch — this is now the third iteration. With τ³-Bench, we're extending it to two new settings: knowledge-intensive retrieval and full-duplex voice. τ-Knowledge: agents must navigate ~700 interconnected policy documents to complete multi-step tasks. Best frontier model (GPT-5.2, high reasoning) hits ~25%. The surprising part: even when you hand the model the exact documents it needs, performance only reaches ~40%.…

    Mar 2026 · its alternatives →

  22. 22

    I built a small benchmark to test CLI coding agents on blind bug detection. A challenger agent injects bugs and writes ground truth (`bugs.json`). A different reviewer agent audits the repo without seeing ground truth, and an LLM matcher scores bug-to-finding assignments. Current run: 50 repos, 150 challenges, 450 reviews, 2,603 injected bugs. Weighted detection: Claude 58.05%, Codex 37.84%, Gemini 27.81%. LLM-judge benchmarks are easy to get wrong, so I’d really appreciate critical feedback on benchmark fairness, scoring/matching methodology, and obvious failure modes I’m missing. Full…

    Feb 2026 · github.com · its alternatives →

  23. 23

    We’re excited to share ML-Dev-Bench, a new open-source benchmark that tests AI agents on real-world ML development tasks. Unlike typical coding challenges or Kaggle-style competitions, our benchmark simulates end-to-end ML workflows including: - Dataset handling and preprocessing - Debugging model and code failures - Implementing new model architectures - Fine-tuning and improving existing models With 30 diverse tasks, ML-Dev-Bench evaluates agents across critical stages of ML development. To complement this, we built Calipers, a framework that provides systematic performance evaluation and…

    2025 · github.com · its alternatives →

  24. 24

    Most inference UIs that I've come across pretty much just give us a chat-like interface to toy around with models in a single visual conversation thread. Given the fact that we are limited to seeing only one output at a time, it's kind of hard to compare outputs from different models, adjustments made to the prompting, and sampler settings. But even when keeping the generation parameters the same (e.g., to test for reliability in the output) and just going for multiple passes, there is no easy way to have a side-by-side comparison to keep track of the outputs from the multiple "rounds". I…

    2024 · github.com · its alternatives →

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