Agentic Coding Benchmark

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.

Model scores 5 models tested

Reset
# 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

What now?

You've seen how models score on Hy-SWE Max Verified (Internal) — here's what to do next.