GameCraft-Bench
Coding agents build playable games end to end inside a real game engine, where scripts, scenes, assets and runtime behavior must work together.
59 upvotes on Hugging Face papers and 213 GitHub stars.
- Made by
- CUHK Shenzhen
- Released
- June 2026
- Kind
- Building whole projects
- Level
- Expert
- Scored
- Checked automatically
- Answers
- Agent task
- Tasks
- All public
- Strongest model tested
- GPT-6 Astra #3 on the capability index
- Last model added
- September 2026
- Scores refreshed
- November 12th, 2026
In the authors’ words
Game generation is an emerging application of coding agents, requiring models to transform natural-language specifications into playable interactive systems. Unlike traditional coding tasks, game generation takes place within a game engine, where scripts, scenes, assets, rendering, and runtime interactions must jointly produce coherent gameplay. We formalize end-to-end game generation as the problem of producing a complete game artifact that realizes a specification through observable player-game interaction in a target environment. We argue that evaluating this setting requires three desiderata: Engine Grounding, Artifact Completeness, and Interactive Verification. We propose an interaction-grounded evaluation framework that assesses executable gameplay through replayed demonstrations and rubric-guided multimodal judging. We instantiate this framework as GameCraft-Bench, a benchmark comprising 140 Godot tasks across 15 game families. Evaluations of frontier coding agents show that end-to-end game generation remains highly challenging: the strongest agent achieves only 41.46%, and most agents score below 40%. Further analysis reveals that while agents often implement recognizable mechanics, they struggle to deliver complete games with sufficient content, functional visual feedback, and coherent presentation. See https://tongxuluo.github.io/gamecraft-bench-website for demos, code, and data.
GPT-6 Astra leads with 75.9% among models released by September 2026
Best score per entry from the benchmark's own leaderboard, read on November 12th, 2026. Where a model ran with several settings or harnesses, we keep its best. Names in gray aren't in our model list: fine-tunes, agent systems, products and older models. They don't count toward leaders.
The newest model with a score here came out in September 2026, and nobody has tested a newer one. Among the 20 highest-ranked models on the capability index, these have no score yet:
- Claude Fable 5.2
-
Gemini 4 Carbon
- GPT-6.1 Sol
- GPT-6.1 Terra
- and 10 more
- 1 GPT-6 Astra xhigh 75.9%
- 2 GPT-6 Sol xhigh 69%
- 3 Claude Opus 5 xhigh 68.4%
- 4 Claude Fable 5 high 65.7%
- 5 GPT-5.6 Sol high 60.5%
- 6 Kimi K3 57%
- 7 Seele02-pro 50.7%
- 8 Claude Opus 4.7 high 41.5%
- 9
DeepSeek V4 Flash 0731 40.6%
- 10 GPT-5.5 high 39.5%
- 11 GLM-5.2 39.1%
- 12 Kimi K2.6 30.6%
- 13 MiMo-V2.5-Pro 24.1%
- 14 GLM-5.1 18.3%
- 15
MiniMax-M2.7 10.9%
- 16
DeepSeek-V4-Pro 2.15%
Source: Official GameCraft-Bench leaderboard
| # | Entry | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | GPT-6 Astra | 75.9% | xhigh, Codex | Sep 2026 | Official leaderboard |
| 2 | GPT-6 Sol | 69% | xhigh, Codex | Sep 2026 | Official leaderboard |
| 3 | Claude Opus 5 | 68.4% | xhigh, Claude Code | Jul 2026 | Official leaderboard |
| 4 | Claude Fable 5 | 65.7% | high, Claude Code | Jun 2026 | Official leaderboard |
| 5 | GPT-5.6 Sol | 60.5% | high, Codex | Jul 2026 | Official leaderboard |
| 6 | Kimi K3 | 57% | Kimi Code | Jul 2026 | Official leaderboard |
| 7 | Seele02-pro | 50.7% | SeeleAgent | Jul 2026 | Official leaderboard |
| 8 | Claude Opus 4.7 | 41.5% | high, Claude Code | Apr 2026 | Official leaderboard |
| 9 | | 40.6% | Claude Code | Jul 2026 | Official leaderboard |
| 10 | GPT-5.5 | 39.5% | high, Codex | Apr 2026 | Official leaderboard |
| 11 | GLM-5.2 | 39.1% | Claude Code | Jun 2026 | Official leaderboard |
| 12 | Kimi K2.6 | 30.6% | Kimi Code | Apr 2026 | Official leaderboard |
| 13 | MiMo-V2.5-Pro | 24.1% | Claude Code | Apr 2026 | Official leaderboard |
| 14 | GLM-5.1 | 18.3% | Code Buddy | Apr 2026 | Official leaderboard |
| 15 | | 10.9% | Code Buddy | Mar 2026 | Official leaderboard |
| 16 | | 2.15% | Codex | Apr 2026 | Official leaderboard |
4 models have held number one on the official leaderboard since its release in June 2026
Lab claims count from the day the card came out, independent runs from the model’s release.
Source: Official GameCraft-Bench leaderboard
Scores over time
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Source: Official GameCraft-Bench leaderboard
No lab model card reports it yet
We read the headline results of 522 launch posts from 52 labs, and none of them list this benchmark.
More in Coding
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DeepSeek-V4-Pro 93.5%
- SWE-bench Multilingual In use 300 GitHub-issue tasks across nine programming languages in SWE-bench format. Patch graded by repository tests. Claude Fable 5.2 96.6%
- DeepSWE In use 113 original long-horizon engineering tasks across 91 repos and five languages, written from scratch. Hand-written verifiers accept alternative solutions. GPT-6 Astra 74.1%
- SciCode In use Scientist-curated research coding problems split into subproblems across natural sciences. Code checked against test cases.
Seed2.1 Pro 59.8%
- Codeforces rating In use Model solves recent Codeforces contest problems. An Elo-style rating is computed from simulated contest performance.
DeepSeek V4.1 Flash 3,471