RealDevWorld Leaderboard

Latest Research in AI Development

Real-World Development Capability Benchmark

Evaluating AI Agents' Performance in Production-Ready Software Engineering with Automated GUI Testing and Interactive Assessment

194 Tasks
4 Categories
92% Accuracy
85% Correlation
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Project Overview

Real-World Tasks

Based on actual application development needs, providing comprehensive evaluation of development capabilities

Multi-Dimensional Evaluation

Assessing AI agent capabilities across requirement understanding, code implementation, debugging, and more

Agent-as-a-Judge Evaluation

Novel evaluation paradigm using autonomous agents for interactive software testing and assessment

Dataset & Evaluation

RealDevBench

A comprehensive real-world development task dataset containing various application development scenarios and task types. This benchmark evaluates AI agents' capabilities across multiple dimensions of software development with automated GUI testing and interactive assessment.

194
Development Tasks
4
Task Categories
Open
Source

Key Features

  • Real-World Scenarios: Actual development challenges
  • Multimodal Tasks: Text, images, audio, and data
  • End-to-End Evaluation: From understanding to debugging
  • Human-Aligned Assessment: 92% expert correlation
Task Type Distribution
Display (50.0%)
Analysis (18.6%)
Game (17.0%)
Data (14.4%)
Access on HuggingFace Dataset Case View Results

Dataset Case Analysis

Dataset Case Analysis

Detailed showcase of typical cases in the RealDevBench dataset, including task types, difficulty distribution, and evaluation criteria.

AppEvalPilot Framework

Research Methodology

Comprehensive research methodology documentation including evaluation framework design, metric definitions, and experimental setup.

Evaluation Pipeline Architecture

AppEvalPilot's three-stage evaluation pipeline: test case generation, interactive execution, and automated assessment with GUI interaction capabilities.

Experimental Results

Performance Analysis Charts

Comparative performance analysis showing different AI Agents and frameworks across multiple evaluation dimensions.

AppEvalPilot Performance Comparison

Method Feature-level Test Case-level Efficiency
Quality Align. Quality Align. Acc. Time Cost
Human 0.74 — 0.65 — — — —
GUI Model
Claude-3.5-Sonnet 0.27 0.23 0.46 0.49 0.68 9.20 1.01
UI-Tars 0.49 0.29 0.63 0.59 0.75 8.65 0.17
GUI Agent Framework
WebVoyager (Qwen2.5) 0.29 0.25 0.35 0.44 0.6 2.16 0.04
WebVoyager (Claude) 0.64 0.43 0.6 0.55 0.74 1.60 0.10
Browser-Use (Claude) 0.67 0.58 0.63 0.61 0.76 13.50 1.13
AppEvalPilot (Claude) 0.73 0.85 0.74 0.81 0.92 9.0 0.26

Performance comparison on RealDevBench benchmark. AppEvalPilot achieves superior performance with 92% accuracy and 85% human correlation, demonstrating significant improvements in evaluation quality and efficiency.

Leaderboard

If you would like to submit your system or model to any of our leaderboards (Products, Open-source & LLM, or Overall), please follow the instructions provided in our submission guide.
Rank Agent Name Model Organization Agent Quality Code Quality Visual Quality
1 MGX (BoN-3) MGX Framework MGX Team 0.78 0.72 0.41
2 Lovable Lovable Framework Lovable Team 0.74 0.58 0.47
3 MGX MGX Framework MGX Team 0.60 0.68 0.41
4 Bolt Bolt Framework StackBlitz 0.54 0.69 0.50
5 Qwen3-Coder-480B Qwen3-Coder-480B Alibaba 0.53 0.41 0.32
6 OpenHands OpenHands Framework OpenHands Team 0.50 0.38 0.33
7 Kimi-K2 Kimi-K2 Moonshot AI 0.39 0.41 0.29
8 Claude-3.7-Sonnet Claude-3.7-Sonnet Anthropic 0.31 0.41 0.18
9 Gemini-2.5-Pro Gemini-2.5-Pro Google 0.29 0.45 0.26
10 DeepSeek-V3 DeepSeek-V3 DeepSeek 0.29 0.18 0.21

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AppEvalPilot Demo & Case Studies

Watch our Agent-as-a-Judge evaluation system in action and explore detailed case studies

AppEvalPilot Agent-as-a-Judge Evaluation

Real-time demonstration of autonomous software evaluation with GUI interaction and automated testing

Key Capabilities

Intelligent Test Generation

Automatically generates comprehensive test cases from software requirements using few-shot learning and domain-specific knowledge

GUI Automation

Executes dynamic user interactions through real GUI operations using PyAutoGUI for mouse and keyboard emulation

Real-time Verification

Performs live functional verification and validates software behavior against requirements with adaptive decision-making

Human-aligned Assessment

Provides accurate evaluations with 92% accuracy and 85% correlation to expert human judgments

View Source Code View Research Details

Case Studies

Expense Planner

An intelligent personal finance tool that helps users track spending, categorize expenses, and set monthly budgets with automatic analytics.

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Festival Planner

An event management application for organising festival schedules, managing performers, venues, and ticketing information interactively.

View Details

Language Spelling Bee

A language-learning quiz platform that offers interactive spelling challenges, real-time feedback, and progress tracking across difficulty levels.

View Details