Hy-SWE Max Verified (Internal)
Tencent internal 300-task agentic coding benchmark; Claude Code scaffold, 200-turn budget, 16 CPU/32 GB sandbox, no web access, avg of 3 runs.
Category
Agentic Coding
Score type
percent
Scale
100%
higher is better
Models tested
5
What is Hy-SWE Max Verified (Internal)?
Hy-SWE Max Verified (Internal) is a benchmark for how well a model works as an autonomous coding agent. The official description says: "Tencent internal 300-task agentic coding benchmark; Claude Code scaffold, 200-turn budget, 16 CPU/32 GB sandbox, no web access, avg of 3 runs". Below we describe in simple words what benchmarks of this type generally examine.
What does it test?
Hy-SWE Max Verified (Internal) 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: Tencent internal 300-task agentic coding benchmark; Claude Code scaffold, 200-turn budget, 16 CPU/32 GB sandbox, no web access, avg of 3 runs.
Frequently asked questions
What is the Hy-SWE Max Verified (Internal) benchmark?
Hy-SWE Max Verified (Internal) is a benchmark for how well a model works as an autonomous coding agent. The official description says: 'Tencent internal 300-task agentic coding benchmark; Claude Code scaffold, 200-turn budget, 16 CPU/32 GB sandbox, no web access, avg of 3 runs'. Below we describe in simple words what benchmarks of this type generally examine.
What does Hy-SWE Max Verified (Internal) test?
Hy-SWE Max Verified (Internal) 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 Hy-SWE Max Verified (Internal) 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 Hy-SWE Max Verified (Internal) 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/hy-swe-max-verified-internal/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 5 models tested
| # | Model | Score | Date | Source | Verified |
|---|---|---|---|---|---|
| 1 |
GLM-5.3
Zhipu AI
|
67.2%
|
28.08.2026 | Tencent Hy4 preview model card benchmark appendix (https://huggingface.co/tencent/Hy4-preview#benchmark-appendix) (Tencent rerun) | Verified |
| 2 |
Kimi K3
Moonshot AI
|
65.6%
|
28.08.2026 | Tencent Hy4 preview model card benchmark appendix (https://huggingface.co/tencent/Hy4-preview#benchmark-appendix) (Tencent rerun) | Verified |
| 3 |
Qwen3.8-2.4T-A95B
Qwen
|
65.2%
|
28.08.2026 | Tencent Hy4 preview model card benchmark appendix (https://huggingface.co/tencent/Hy4-preview#benchmark-appendix) (Tencent rerun) | Verified |
| 4 |
Hy4 preview
Tencent
|
64.2%
|
28.08.2026 | Tencent Hy4 preview model card benchmark appendix (https://huggingface.co/tencent/Hy4-preview#benchmark-appendix) | Verified |
| 5 |
Hy3
Tencent
|
49%
|
28.08.2026 | Tencent Hy4 preview model card benchmark appendix (https://huggingface.co/tencent/Hy4-preview#benchmark-appendix) | Verified |