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SWE-bench Verified

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A primer on self-improving agent harnesses TLDR Dev · 2 weeks ago · 3

CoderForge-Preview: SOTA open dataset for training efficient coding agents Together AI · 5 months ago · 1

Why we no longer evaluate SWE-bench Verified OpenAI Blog · 5 months ago · 26

Introducing SWE-bench Verified OpenAI Blog · 1 year ago · 50

Timeline

Month Quarter Year

2026

Development of autonomous agent harness frameworks for improving large language model reliability and performance Feature update

2024

13 Aug Introducing SWE-bench Verified

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Derived from SWE-bench · 1 source
HarnessX integrated with this model · 1 source

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TLDRocket 3 August 2026

Open-source AI models are consolidating their foothold as the dominant deployment pattern, even as frontier capabilities remain concentrated at a handful of well-funded labs. Interconnects launched the Artifacts Hub and Adoption Dashboard to track 792 open-weight models released in two years, mapping adoption by geography and revealing how deeply DeepSeek and Chinese models have penetrated deployment pipelines globally. Meanwhile, DeepSeek itself proved that scale isn't everything: its V4-Flash model, a leaner 284-billion-parameter variant, outperformed its own flagship on agent benchmarks through careful post-training. The MIT-licensed release lets enterprises avoid vendor lock-in entirely, directly controlling deployment and retraining at lower infrastructure cost.

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