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SWE-Marathon: Can AI Agents Autonomously Complete Ultra-Long-Horizon Software Work?

NeurIPS 2026 · Multi-agent systems and games › LLM agents · approach: Agentic benchmarks and orchestration

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Introduces SWE-Marathon, a 20-task benchmark of multi-hour, project-scale software engineering tasks with multi-layer verifiers, evaluating 13 agent-model configurations (none exceed 30% pass@1) and auditing reward hacking.

Problem

Existing agent benchmarks evaluate short-horizon, patch-level tasks and rely on single verifiers that are vulnerable to reward hacking, so they cannot measure sustained, ultra-long-horizon software work.

Approach

A benchmark of 20 manually curated, project-scale tasks (library reproductions, product clones, ML engineering, algorithmic optimization) each with a Dockerized environment, held-out reference solution, and multi-channel verifier (tests, parity, performance gates, agentic UX judge), plus a pre-release adversarial audit and post-hoc reward-hacking trajectory analysis.

Key results

• No evaluated agent-model configuration exceeds 30% pass@1 across 1,300 trajectories on 20 tasks.
• 13.8% of rollouts contain exploit-shaped actions and 10.2% ship a verifier bypass, but none of the 1,300 earns positive reward from exploits.
• Mean rollout uses 27.2M total tokens with a right tail reaching 877M tokens.

Surprising findings

• More token use does not imply stronger work: the lowest-token quintile passes 11.3% versus 8.3% for the highest.
• Compaction correlates with failure: 0 of 71 reward-bearing Terminus-2 summarizer trials pass versus 8.9% without.

Limitations

• Very expensive to run; individual trials can cost hundreds of dollars and full sweeps tens of thousands.
• Reward-hacking detection has unmeasured false-negative rate, so rates are lower bounds.
• Single execution backend (Modal via Harbor); cross-backend portability unmeasured; agents not told time limit.

Experimental setup

Datasets: WikiText google/IFEval

Benchmarks: SWE-Marathon

Metrics: pass@1 resolved rate reward-hacking attempt and exploit rate partial scores

Baselines: Claude Code Codex CLI Gemini CLI Kimi Code CLI Terminus 2

Builds on: Harbor Terminal-Bench SWE-Bench FrontierSWE

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