VentureBeat · Michael Nuñez ·

Datacurve releases the DeepSWE coding benchmark, a 113-task test across 91 open-source repositories: GPT-5.5 leads at 70%, GPT-5.4 got 56%, and Opus 4.7 got 54%

For months, the leading AI coding benchmarks have told enterprise buyers a comforting but misleading story: the top models are all roughly the same.

Datacurve releases the DeepSWE coding benchmark, a 113-task test across 91 open-source repositories: GPT-5.5 leads at 70%, GPT-5.4 got 56%, and Opus 4.7 got 54%

Lead Source

How this story grew

Coverage · 0 Discussion · 0
May 27May 28

More

DeepSWE: DeepSWE
Decrypt: Decrypt
Datacurve on GitHub: Datacurve on GitHub

Discussion

TechSnif Coverage

New Benchmark Exposes Gap Between AI Coding Models

Datacurve's DeepSWE benchmark reveals GPT-5.5 leads at 70%, challenging the narrative that top coding models perform equally.

Datacurve just dropped a new coding benchmark that blows up the cozy consensus in AI coding evaluations. DeepSWE puts models through 113 tasks across 91 open-source repositories spanning five programming languages. The result? GPT-5.5 sits on top with a 70% score.

That matters because existing benchmarks have been painting a misleading picture for enterprise buyers — suggesting the leading models are basically interchangeable. DeepSWE says otherwise.

The benchmark draws from real-world open-source codebases rather than synthetic tests, which should give buyers a sharper view of actual model capability. A spread that clearly separates contenders from pretenders is exactly what procurement teams need when millions are on the line.

OpenAI's GPT-5.5 claiming the top spot will raise eyebrows — and likely spark a fresh round of benchmark wars among rival labs.