Harbor-Index
Agentic coding index benchmark reported in the Tencent Hy4 preview model card benchmark appendix.
Category
Agentic Coding
Score type
percent
Scale
100%
higher is better
Models tested
4
What is Harbor-Index?
Harbor-Index is a benchmark for how well a model works as an autonomous coding agent. The official description says: "Agentic coding index benchmark reported in the Tencent Hy4 preview model card benchmark appendix". Below we describe in simple words what benchmarks of this type generally examine.
What does it test?
Harbor-Index measures how well a model works as an autonomous coding agent. In detail, it checks:
- fixing real, open bugs from real software repositories
- planning multi-step changes, running commands and editing files by itself
- passing the project's test suite after its changes
- handling whole repositories, not just small isolated code snippets
How to read the score
The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better.
Official methodology note: Agentic coding index benchmark reported in the Tencent Hy4 preview model card benchmark appendix.
Frequently asked questions
What is the Harbor-Index benchmark?
Harbor-Index is a benchmark for how well a model works as an autonomous coding agent. The official description says: 'Agentic coding index benchmark reported in the Tencent Hy4 preview model card benchmark appendix'. Below we describe in simple words what benchmarks of this type generally examine.
What does Harbor-Index test?
Harbor-Index mainly measures how well a model works as an autonomous coding agent. Concretely, it checks: fixing real, open bugs from real software repositories; planning multi-step changes, running commands and editing files by itself; passing the project's test suite after its changes.
How is the Harbor-Index score calculated?
The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better. The declared maximum score of this benchmark is 100.0.
Where do I get Harbor-Index data and scores?
The official benchmark page/reference is linked on this page. Every score on Open LLM Radar is also available as open data: download the scores JSON (http://open-llm-radar-api:8000/api/v1/benchmarks/harbor-index/scores) or pull it directly from the Open LLM Radar API with any HTTP client.
Benchmark data & downloads
Where to get, inspect and reuse the data behind this benchmark.
Model scores 4 models tested
| # | Model | Score | Date | Source | Verified |
|---|---|---|---|---|---|
| 1 |
GLM-5.3
Zhipu AI
|
42.5%
|
28.08.2026 | Tencent Hy4 preview model card benchmark appendix (https://huggingface.co/tencent/Hy4-preview#benchmark-appendix) (Tencent rerun) | Verified |
| 2 |
Hy4 preview
Tencent
|
39.6%
|
28.08.2026 | Tencent Hy4 preview model card benchmark appendix (https://huggingface.co/tencent/Hy4-preview#benchmark-appendix) | Verified |
| 3 |
Qwen3.8-2.4T-A95B
Qwen
|
38.8%
|
28.08.2026 | Tencent Hy4 preview model card benchmark appendix (https://huggingface.co/tencent/Hy4-preview#benchmark-appendix) (Tencent rerun) | Verified |
| 4 |
Hy3
Tencent
|
15.6%
|
28.08.2026 | Tencent Hy4 preview model card benchmark appendix (https://huggingface.co/tencent/Hy4-preview#benchmark-appendix) | Verified |