TensorBench - API: leaderboard

TensorBench (2026) tests coding agents (a published CLI harness with its model) on feature-addition and refactoring tasks in Scorch, a compiler-based tensor framework with dense and sparse tensors; a task passes when the patched repository passes its randomized regression tests and the tests the agent adds. This board is the pass rate in percent on the 99 user-facing API tasks, such as linear algebra, constructors, shape operations and ML primitives; higher is better.

Metric: Pass rate (%) on the 99 user-facing API tasks (linear algebra, constructors and I/O, shape and layout, elementwise math, ML primitives and more); each coding agent (a published CLI scaffold with its model) edits the open-source Scorch compiler-based tensor framework inside a per-task container, one run per task; a task passes when every test of the post-patch suite (pre-existing randomized regression tests plus the tests the agent adds) succeeds; higher is better. Source: arxiv.org. Saturation forecast: Around February 2027. 7 models tracked.

Top models

#ModelScoreOverall rank
1GPT-5.5 (xHigh)63.6#49 (GPT-5.5)
2Claude Opus 4.7 (xHigh)61.6#79 (Claude Opus 4.7)
3GPT-5.3 Codex (xHigh)51.5#116 (GPT-5.3 Codex)
4Claude Opus 4.649.5#102
5GPT-5.4 (xHigh)45.5#123 (GPT-5.4)
6Gemini 3.1 Pro (Preview)37.4#94
7Qwen 3 Coder 480B A35B Instruct14.1#643

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=tensorbench-api · How It Works · Data refreshed daily, snapshot 2026-11-13.