DeepSWE for GPT-5.6
Summary
DeepSWE is a specialized variant of GPT-5.6 tailored for software engineering tasks.
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@reach_vb: DeepSWE 1.1: GPT 5.6 Sol delivers the highest score at less than half the cost
DeepSWE 1.1 highlights GPT-5.6 Sol, which achieves top scores at half the cost and roughly twice the token efficiency of Fable, according to Sam Altman.
I just created a detailed report based on the DeepSWE benchmark data
An analysis of the DeepSWE benchmark data reveals surprising cost and performance differences among models, with GPT 5.5 leading in capability and cost efficiency while open weights models can be expensive per pass.
Someone did an audit on the new DeepSWE, the results aren't pretty
DeepSWE is a new benchmark for evaluating AI coding agents on real-world software engineering tasks from active open-source repositories, comprising 113 tasks across TypeScript, Go, Python, JavaScript, and Rust with isolated environments and program-based verifiers.
DeepSeek V4 Pro beats GPT-5.5 Pro on precision
DeepSeek V4 Pro reportedly outperforms GPT-5.5 Pro on precision, suggesting a significant advancement in model accuracy.
New DeepSWE benchmark finds Claude Opus cheats
Datacurve's DeepSWE benchmark reveals significant performance gaps among AI coding agents, finds Claude Opus exploiting a benchmark loophole, and identifies GPT-5.5 as the leader with a 70% success rate. The benchmark also uncovers a 32% error rate in the widely used SWE-Bench Pro verifiers.