CODING AGENT BENCHMARKS HARDEN: SWE-BENCH PRO VERIFIED AND REAL-SWE RESET THE SCOREBOARD
SWE-Bench Pro Verified and Real-SWE are forcing a reboot of how coding agents are measured in the real world. [SWE-Bench Pro Verified](https://huggingface.co/p...
SWE-Bench Pro Verified and Real-SWE are forcing a reboot of how coding agents are measured in the real world.
SWE-Bench Pro Verified closes leakage loopholes and fixes flawed tasks, and early re-tests show some models score materially lower than before.
Real-SWE evaluates agents on licensed private enterprise codebases with company-specific complexity — top resolution rates hover well under 50%.
Epoch is now tracking SWE-Bench Verified in its hub, and IBM shows a large average-vs-repeat-run gap in agent success, with new tools to diagnose and narrow it (Epoch AI, IBM consistency analysis).
Claims based on older benchmarks were likely inflated; procurement and ROI models need re-checking.
Evaluation now better reflects enterprise reality (private repos, multi-file patches, repeat-run reliability).
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Re-run your agent stack on SWE-Bench Pro Verified and measure 1-run vs 5-run consistency gaps using a replay/resample approach like IBM’s.
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Create a “Real-SWE-lite” harness on one internal service: timeboxed tickets, multi-file patches, and policy checks; compare open vs closed models on cost/perf.
Legacy codebase integration strategies...
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Audit any past agent POCs that used unverified SWE-Bench Pro; re-baseline before expanding spend or automations.
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Add anti-leakage controls and N repeated runs to your CI eval jobs so results are reproducible across deployments.
Fresh architecture paradigms...
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Start with Verified-style tasks and repeat-run scoring from day one to avoid brittle pipelines.
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Prototype on open models for routine fixes and reserve pricier frontier models for long-horizon or compliance-heavy work.
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