A test run is a single execution of a benchmark test using a defined model configuration.
Each run represents how a particular large language model (LLM) — such as GPT-4, Claude-3, or Gemini — performed on a given task at a specific time, with specific settings.
A test run includes:
Together, test runs make it possible to compare models, providers, and configurations across benchmarks in a transparent and reproducible way.
{'document-type': ['newspaper-page'], 'century': [18], 'language': ['en'], 'task': ['data-correction']}
| Provider | openrouter |
| Model | qwen/qwen3-vl-8b-instruct |
| Temperature | 0.0 |
| Dataclass | CorrectedAdvert |
| Normalized Score | 100.00 % |
| Test time | unknown seconds |
Fix this xml. Add xml-tags if faulty where it makes sense.
Format your response as JSON. Use the keys 'fixed_xml', 'number_of_fixes', 'explanation'.
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 72.41 | n/a | n/a | n/a | n/a | n/a | n/a | n/a | n/a |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: n/a, n/a. | Tokens: 35.3K IT + 23.7K OT = 59.1K TT | Cost: 0.003$ + 0.012$ = 0.015$ |
{'document-type': ['newspaper-page'], 'century': [18], 'language': ['en'], 'task': ['data-correction']}
| Provider | openai |
| Model | gpt-5-mini-2025-08-07 |
| Temperature | 1.0 |
| Dataclass | CorrectedAdvert |
| Normalized Score | 100.00 % |
| Test time | unknown seconds |
Fix this xml. Add xml-tags if faulty where it makes sense.
Format your response as JSON. Use the keys 'fixed_xml', 'number_of_fixes', 'explanation'.
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 91.78 | n/a | n/a | n/a | n/a | n/a | n/a | n/a | n/a |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: n/a, n/a. | Tokens: 33.6K IT + 189.5K OT = 223.1K TT | Cost: 0.008$ + 0.379$ = 0.387$ |
{'document-type': ['newspaper-page'], 'century': [18], 'language': ['en'], 'task': ['data-correction']}
| Provider | openai |
| Model | gpt-5-2025-08-07 |
| Temperature | 1.0 |
| Dataclass | CorrectedAdvert |
| Normalized Score | 100.00 % |
| Test time | unknown seconds |
Fix this xml. Add xml-tags if faulty where it makes sense.
Format your response as JSON. Use the keys 'fixed_xml', 'number_of_fixes', 'explanation'.
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 94.99 | n/a | n/a | n/a | n/a | n/a | n/a | n/a | n/a |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: n/a, n/a. | Tokens: 33.6K IT + 270.6K OT = 304.2K TT | Cost: 0.042$ + 2.706$ = 2.748$ |
{'document-type': ['newspaper-page'], 'century': [18], 'language': ['en'], 'task': ['data-correction']}
| Provider | mistral |
| Model | magistral-small-2509 |
| Temperature | 0.0 |
| Dataclass | CorrectedAdvert |
| Normalized Score | 100.00 % |
| Test time | unknown seconds |
Fix this xml. Add xml-tags if faulty where it makes sense.
Format your response as JSON. Use the keys 'fixed_xml', 'number_of_fixes', 'explanation'.
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 75.65 | n/a | n/a | n/a | n/a | n/a | n/a | n/a | n/a |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: n/a, n/a. | Tokens: 40.3K IT + 32.8K OT = 73.1K TT | Cost: 0.020$ + 0.016$ = 0.037$ |
{'document-type': ['newspaper-page'], 'century': [18], 'language': ['en'], 'task': ['data-correction']}
| Provider | openai |
| Model | gpt-4.1-2025-04-14 |
| Temperature | 0.0 |
| Dataclass | CorrectedAdvert |
| Normalized Score | 100.00 % |
| Test time | unknown seconds |
Fix this xml. Add xml-tags if faulty where it makes sense.
Format your response as JSON. Use the keys 'fixed_xml', 'number_of_fixes', 'explanation'.
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 94.74 | n/a | n/a | n/a | n/a | n/a | n/a | n/a | n/a |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: n/a, n/a. | Tokens: 33.9K IT + 61.7K OT = 95.6K TT | Cost: 0.068$ + 0.493$ = 0.561$ |
{'document-type': ['newspaper-page'], 'century': [18], 'language': ['en'], 'task': ['data-correction']}
| Provider | openai |
| Model | gpt-4.1-nano-2025-04-14 |
| Temperature | 0.0 |
| Dataclass | CorrectedAdvert |
| Normalized Score | 100.00 % |
| Test time | unknown seconds |
Fix this xml. Add xml-tags if faulty where it makes sense.
Format your response as JSON. Use the keys 'fixed_xml', 'number_of_fixes', 'explanation'.
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 92.56 | n/a | n/a | n/a | n/a | n/a | n/a | n/a | n/a |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: n/a, n/a. | Tokens: 33.8K IT + 57.1K OT = 90.9K TT | Cost: 0.003$ + 0.023$ = 0.026$ |
{'document-type': ['newspaper-page'], 'century': [18], 'language': ['en'], 'task': ['data-correction']}
| Provider | openrouter |
| Model | meta-llama/llama-4-maverick |
| Temperature | 0.0 |
| Dataclass | CorrectedAdvert |
| Normalized Score | 100.00 % |
| Test time | unknown seconds |
Fix this xml. Add xml-tags if faulty where it makes sense.
Format your response as JSON. Use the keys 'fixed_xml', 'number_of_fixes', 'explanation'.
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 75.91 | n/a | n/a | n/a | n/a | n/a | n/a | n/a | n/a |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: n/a, n/a. | Tokens: 32.1K IT + 26.9K OT = 59.0K TT | Cost: 0.005$ + 0.016$ = 0.021$ |
{'document-type': ['newspaper-page'], 'century': [18], 'language': ['en'], 'task': ['data-correction']}
| Provider | anthropic |
| Model | claude-opus-4-5-20251101 |
| Temperature | 0.0 |
| Dataclass | CorrectedAdvert |
| Normalized Score | 100.00 % |
| Test time | unknown seconds |
Fix this xml. Add xml-tags if faulty where it makes sense.
Format your response as JSON. Use the keys 'fixed_xml', 'number_of_fixes', 'explanation'.
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 96.96 | n/a | n/a | n/a | n/a | n/a | n/a | n/a | n/a |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: n/a, n/a. | Tokens: 74.1K IT + 35.8K OT = 109.9K TT | Cost: 0.370$ + 0.895$ = 1.265$ |
{'document-type': ['newspaper-page'], 'century': [18], 'language': ['en'], 'task': ['data-correction']}
| Provider | mistral |
| Model | mistral-small-2506 |
| Temperature | 0.0 |
| Dataclass | CorrectedAdvert |
| Normalized Score | 100.00 % |
| Test time | unknown seconds |
Fix this xml. Add xml-tags if faulty where it makes sense.
Format your response as JSON. Use the keys 'fixed_xml', 'number_of_fixes', 'explanation'.
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 93.45 | n/a | n/a | n/a | n/a | n/a | n/a | n/a | n/a |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: n/a, n/a. | Tokens: 40.3K IT + 30.1K OT = 70.4K TT | Cost: 0.004$ + 0.009$ = 0.013$ |
{'document-type': ['newspaper-page'], 'century': [18], 'language': ['en'], 'task': ['data-correction']}
| Provider | genai |
| Model | gemini-2.5-flash-lite |
| Temperature | 0.0 |
| Dataclass | CorrectedAdvert |
| Normalized Score | 100.00 % |
| Test time | unknown seconds |
Fix this xml. Add xml-tags if faulty where it makes sense.
Format your response as JSON. Use the keys 'fixed_xml', 'number_of_fixes', 'explanation'.
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 61.80 | n/a | n/a | n/a | n/a | n/a | n/a | n/a | n/a |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: n/a, n/a. | Tokens: 31.5K IT + 1.1M OT = 1.2M TT | Cost: 0.003$ + 0.459$ = 0.462$ |