Benchmark Almanac

GameCraft-Bench

GPT-6 Astra 75.9% leads since September 2026
Not in model cards

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.

Abstract of GameCraft-Bench: Can Agents Build Playable Games End-to-End in a Real Game Engine? (arXiv:2606.17861, CC0)
16
Entries on its own leaderboard, 15 models we track

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:

  1. 1 GPT-6 Astra xhigh 75.9%
  2. 2 GPT-6 Sol xhigh 69%
  3. 3 Claude Opus 5 xhigh 68.4%
  4. 4 Claude Fable 5 high 65.7%
  5. 5 GPT-5.6 Sol high 60.5%
  6. 6 Kimi K3 57%
  7. 7 Seele02-pro 50.7%
  8. 8 Claude Opus 4.7 high 41.5%
  9. 9 DeepSeek V4 Flash 0731 40.6%
  10. 10 GPT-5.5 high 39.5%
  11. 11 GLM-5.2 39.1%
  12. 12 Kimi K2.6 30.6%
  13. 13 MiMo-V2.5-Pro 24.1%
  14. 14 GLM-5.1 18.3%
  15. 15 MiniMax-M2.7 10.9%
  16. 16 DeepSeek-V4-Pro 2.15%

Source: Official GameCraft-Bench leaderboard

#EntryScoreSettingDateSource
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 DeepSeek V4 Flash 0731 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 MiniMax-M2.7 10.9% Code Buddy Mar 2026 Official leaderboard
16 DeepSeek-V4-Pro 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.

Anthropic OpenAI
Own leaderboard Not tested since Sep 2026
GPT-6 Astra 75.9%

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.

On the benchmark’s own leaderboard Best so far
0% 20% 40% 60% 80% 100% 2026 Near the ceiling (85%) GPT-6 Astra Claude Opus 5 Claude Opus 4.7 GLM-5.1 MiniMax-M2.7 0% 20% 40% 60% 80% 100% 2026 Near the ceiling (85%) GPT-6 Astra Claude Opus 5

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.

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  • 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