# APEX-Agents ![Category](https://img.shields.io/badge/Category-Agent%20%2F%20Professional%20Tasks-1f6feb) ![Metric](https://img.shields.io/badge/Metric-%25%20Success-2da44e) ![Saturation](https://img.shields.io/badge/Saturation-Low-d29922) ![Created](https://img.shields.io/badge/Created-2026-555) [![Dataset](https://img.shields.io/badge/Dataset-HuggingFace-ff9d00?logo=huggingface&logoColor=white)](https://huggingface.co/datasets/mercor/apex-agents) > **Quick answer:** APEX-Agents is a professional-grade agentic task benchmark from Mercor, a talent and evaluation platform, testing AI agents on economically valuable, real-world knowledge-work workflows. It's designed to complement broader agent benchmarks by focusing on tasks that mirror actual professional work. Kimi K3 scores 41.0% as of July 2026. ## At a Glance **What it tests:** An AI agent's ability to complete professional-grade knowledge-work tasks end-to-end, evaluated against Mercor's curated task pool. **Why it matters:** Mercor's evaluation network draws on real hiring and workforce data, giving APEX-Agents a grounding in genuinely economically valuable work rather than synthetic agent tasks. **Known limitations:** As a vendor-curated benchmark without a published academic paper, methodology details are less transparent than peer-reviewed benchmarks. ## What APEX-Agents Measures APEX-Agents evaluates AI agents on professional-grade tasks curated by Mercor, spanning knowledge-work domains that reflect real hiring and workforce assessment scenarios. Tasks are designed to test sustained, multi-step task completion rather than single-turn question answering, aligning with how agents would be deployed in real professional contexts. ## Benchmark Specifications | Field | Value | |---|---| | Task category | Agent / professional knowledge work | | Metric | % task success | | Saturation | Low | | Created by | Mercor | | Dataset | [mercor/apex-agents on HuggingFace](https://huggingface.co/datasets/mercor/apex-agents) | ## How APEX-Agents Is Scored Agents attempt each professional-grade task, and outcomes are verified against Mercor's task-specific success criteria, producing an aggregate % task success rate. ## State-of-the-Art Results | Rank | Model | Score | Source | Date | |---|---|---|---|---| | 1 | [Kimi K3](/models/moonshot/kimi-k3) | 41.0% | [Kimi K3 technical report](https://www.kimi.com/blog/kimi-k3) | 2026-07 | *Score sourced from Moonshot AI's Kimi K3 announcement, July 2026.* ## APEX-Agents on Benchgen > No Benchgen results yet — [be the first to run APEX-Agents](/benchmarks/mercor/apex-agents). ## APEX-Agents vs Other Benchmarks | Benchmark | What it tests | Saturation | |---|---|---| | **APEX-Agents** | Professional-grade knowledge-work agent tasks | Low | | [Agents' Last Exam](/benchmarks/berkeley/agents-last-exam) | Economically valuable long-horizon agent tasks | Low | | [JobBench](/benchmarks/platform/jobbench) | Job/workforce-oriented agent tasks | Low | | [MCP Atlas](/benchmarks/scale-ai/mcp-atlas) | MCP tool-use agentic workflows | Low | ## Run APEX-Agents on Your Model Benchgen lets you run APEX-Agents against your own model and harness, tracking professional-task success rates over time to validate agent deployments before production rollout. ## Frequently Asked Questions

What is APEX-Agents?

APEX-Agents is a professional-grade agentic task benchmark from Mercor, testing AI agents on economically valuable, real-world knowledge-work workflows.

What does a good score look like on APEX-Agents?

Kimi K3 reports 41.0% as of July 2026. Given the professional-grade difficulty of the task pool, scores in the 40%+ range represent frontier-level agentic performance.

Who created APEX-Agents?

APEX-Agents is created and maintained by Mercor, a talent and workforce evaluation platform that curates professional-grade agentic benchmarks.

Rank	Model	Score
1	grok-4-6	57.5
2	kimi-k3	41
3	solar-pro-4	18.7

APEX-Agents — Results

APEX-Agents — Leaderboard

APEX-Agents Leaderboard