GBA-Eval
We show this table for reference; we do not rank on it.
An agentic coding benchmark that asks models to build a Game Boy Advance emulator from scratch and grades emulator behavior against procedural, audio, and gameplay tests.
Overall score on GBA-Eval — May 30, 2026
We mirror the published overall score view for GBA-Eval. Claude Opus 4.8 leads the public snapshot at 70.9%, followed by GPT-5.5 (53.2%) and Claude Sonnet 4.6 (48.8%). We do not use these results to rank models overall.
Claude Opus 4.8
Anthropic
GPT-5.5
OpenAI
Claude Sonnet 4.6
Anthropic
14 modelsCodingCurrentDisplay onlyUpdated May 30, 2026
Overall score table (14 models)
ScoreHow GBA-Eval is shown here
BenchLM mirrors the official GBA-Eval leaderboard snapshot graded on May 30, 2026. The benchmark asks coding agents to build a Game Boy Advance emulator and scores the result against 27 procedural, audio, and gameplay test cases.
GBA-Eval is display only on BenchLM. The source rows are agentic software-engineering runs with large token budgets and verifier-specific emulator tests, so BenchLM does not fold them into model-only weighted rankings.
Snapshot
The published GBA-Eval snapshot places Claude Opus 4.8 first at 70.9%. The third row is 22.1 points behind. The broader top-10 range is 70.0 points, so the table still separates the published systems.
14 models have been evaluated on GBA-Eval. The benchmark falls in the Coding category. We keep external benchmark mirrors separate from the weighted global scoring system, so these results remain source-specific evidence. GBA-Eval is currently displayed for reference but excluded from the scoring formula, so it does not directly affect overall rankings.
About GBA-Eval
Year
2026
Tasks
27 emulator test cases
Format
Overall emulator score
Difficulty
Long-horizon systems programming
GBA-Eval evaluates long-horizon coding agents by having them implement a working GBA emulator. The public leaderboard reports overall scores across 27 test cases with token usage and checkpoints preserved in the source JSON feed.
Freshness and provenance
Version
GBA-Eval 2026
Refresh cadence
Quarterly
Staleness state
Current
Question availability
Public benchmark set
BenchLM uses freshness metadata to decide whether a benchmark should still be treated as a strong differentiator, a benchmark to watch, or a display-only reference. For the full scoring policy, see the BenchLM methodology page.
Questions
What does GBA-Eval measure?
An agentic coding benchmark that asks models to build a Game Boy Advance emulator from scratch and grades emulator behavior against procedural, audio, and gameplay tests.
Which model leads the published GBA-Eval snapshot?
Claude Opus 4.8 currently leads the published GBA-Eval snapshot with 70.9% overall score. BenchLM shows this benchmark for display only and does not use it in overall rankings.
How many models are evaluated on GBA-Eval?
The May 30, 2026 snapshot contains 14 AI models.
Know when it’s worth switching models
The model to choose, the cheaper alternative, and the release we would wait on.
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