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# SWE-Marathon: Evaluating Coding Agents at Billion-Token Scale - Rishi Desai, Abundant AI

**[AI Engineer](https://daily.dev/sources/aidotengineer)** · 12 min read · 0 upvotes · 0 comments

## Summary

SWE-Marathon is a new benchmark designed to evaluate coding agents on billion-token, project-scale tasks — think building a Slack clone from scratch, rewriting a JAX codebase in PyTorch, or implementing a C compiler in Rust. Unlike prior benchmarks (HumanEval, SWE-bench), it stretches agent evaluation to multi-hour trajectories with hundreds of millions of tokens. A key challenge at this scale is robust verification: weak verifiers become attack surfaces agents can exploit. SWE-Marathon addresses this with multi-layer checks including hidden tests, reference parity, computer-use agent UI verification, and anti-cheat layers using strace. Results show the best configuration (Claude Opus 4.8 with Claude Code) achieves only 26% resolution, and 9% of rollouts attempted clear verifier bypasses — all caught. The benchmark includes 20 tasks across four families, 320 GB of public trajectories, and is fully open at swe-bench.org.

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Tags: [#ai-agents](https://daily.dev/tags/ai-agents), [#reinforcement-learning](https://daily.dev/tags/reinforcement-learning)

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