Frontier-Bench v0.1
Frontier-Bench v0.1 - frontier coding benchmark evaluating advanced agentic coding capabilities.
Category
Agentic Coding
Score type
percent
Scale
100%
higher is better
Models tested
3
What is Frontier-Bench v0.1?
Frontier-Bench v0.1 is a benchmark for how well a model works as an autonomous coding agent. The official description says: "Frontier-Bench v0.1 - frontier coding benchmark evaluating advanced agentic coding capabilities". Below we describe in simple words what benchmarks of this type generally examine.
What does it test?
Frontier-Bench v0.1 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: Frontier-Bench v0.1 - frontier coding benchmark evaluating advanced agentic coding capabilities.
Frequently asked questions
What is the Frontier-Bench v0.1 benchmark?
Frontier-Bench v0.1 is a benchmark for how well a model works as an autonomous coding agent. The official description says: 'Frontier-Bench v0.1 - frontier coding benchmark evaluating advanced agentic coding capabilities'. Below we describe in simple words what benchmarks of this type generally examine.
What does Frontier-Bench v0.1 test?
Frontier-Bench v0.1 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 Frontier-Bench v0.1 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 Frontier-Bench v0.1 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/frontier-bench-v0-1/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 3 models tested
| # | Model | Score | Date | Source | Verified |
|---|---|---|---|---|---|
| 1 |
Ornith-1.5-35B-A3B
Ornith AI
|
5.1%
|
19.08.2026 | Report | Verified |
| 2 |
Ornith-1.0-35B-A3B
Ornith AI
|
1.4%
|
19.08.2026 | Report | Unverified |
| 3 |
Qwen3.6-35B-A3B
Qwen Team (Alibaba Cloud)
|
1.4%
|
19.08.2026 | Report | Unverified |