GDPx v1.0 - Materials Science - Emulated - Default Score: leaderboard

GDPx v1.0 Materials Science - Emulated - Default Score measures professional agent work using the publisher's native task-specific scores on a 0–100 scale. Three attempts are run per task, normally with an eight-hour limit. Scores mix binary and continuous grading; the overall mean weights eleven domains equally and partners equally within each domain. Native harness, effort and assigned/scored counts remain separate; missing native scores are not treated as zero.

Metric: Default Score (%). Source: gdpx.semianalysis.com. Saturation forecast: Rough model projection: around 2026. 20 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 4 Carbon (GDPx Run: v1.0; gemini-4-carbon; Antigravity; effort High)26.17
2GPT-6.1 Sol (GDPx Run: v1.0; gpt-6-1-sol; Codex; effort Max)17.98
3GPT-6 Astra (GDPx Run: v1.0; gpt-6-astra; Codex; effort Max)16.51
4Claude Opus 5.5 (GDPx Run: v1.0; claude-opus-5-5; Claude Code; effort Max)16.37
5GPT-6.1 Terra (GDPx Run: v1.0; gpt-6-1-terra; Codex; effort Max)15.98
6Claude Sonnet 5.5 (GDPx Run: v1.0; claude-sonnet-5-5; Claude Code; effort Max)15.13
7Claude Fable 5.1 (GDPx Run: v1.0; claude-fable-5-1; Claude Code; effort Max)11.99
8Muse Wonder Full (GDPx Run: v1.0; muse-wonder-full; Muse Code; effort Highest)11.95
9Muse Wonder (GDPx Run: v1.0; muse-wonder; Muse Code; effort Highest)10.83
10Gemini 4 Argon (GDPx Run: v1.0; gemini-4-argon; Antigravity; effort High)10.42

Interactive version: theaggregate.ai/benchmark?slug=gdpx-v1-0-materials-science-emulated-default-score · How It Works · Data refreshed daily, snapshot 2026-11-05.