GDPx v1.0 - Software Engineering - Datacurve - Default Score: leaderboard

GDPx v1.0 Software Engineering - Datacurve - 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
1Claude Sonnet 5.5 (GDPx Run: v1.0; claude-sonnet-5-5; Claude Code; effort Max)11.11
2Gemini 4 Carbon (GDPx Run: v1.0; gemini-4-carbon; Antigravity; effort High)11.11
3GPT-6.1 Terra (GDPx Run: v1.0; gpt-6-1-terra; Codex; effort Max)11.11
4Claude Opus 5.5 (GDPx Run: v1.0; claude-opus-5-5; Claude Code; effort Max)8.89
5Gemini 4 Argon (GDPx Run: v1.0; gemini-4-argon; Antigravity; effort High)8.89
6GPT-6.1 Sol (GDPx Run: v1.0; gpt-6-1-sol; Codex; effort Max)8.89
7Claude Haiku 5.5 (GDPx Run: v1.0; claude-haiku-5-5; Claude Code; effort Max)6.67
8GPT-6 Astra (GDPx Run: v1.0; gpt-6-astra; Codex; effort Max)6.67
9Claude Fable 5.1 (GDPx Run: v1.0; claude-fable-5-1; Claude Code; effort Max)4.44
10MiniMax-M3.1-Flash (GDPx Run: v1.0; minimax-m3-1-flash; MCode; effort Highest)2.22

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