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 | openai |
| Model | gpt-5.3-codex |
| Temperature | 1.0 |
| Dataclass | not set (=no auto-parsed result) |
| 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 | |||||
| 97.12 | 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: 27.9K IT + 30.6K OT = 58.5K TT | Cost: 0.049$ + 0.428$ = 0.477$ |
{'document-type': ['newspaper-page'], 'century': [18], 'language': ['en'], 'task': ['data-correction']}
| Provider | anthropic |
| Model | claude-sonnet-4-6 |
| 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 | |||||
| 96.55 | 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 + 46.3K OT = 120.4K TT | Cost: 0.222$ + 0.695$ = 0.917$ |
{'document-type': ['newspaper-page'], 'century': [18], 'language': ['en'], 'task': ['data-correction']}
| Provider | anthropic |
| Model | claude-opus-4-6 |
| 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 | |||||
| 97.46 | 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 + 41.3K OT = 115.4K TT | Cost: 0.371$ + 1.032$ = 1.403$ |
{'document-type': ['newspaper-page'], 'century': [18], 'language': ['en'], 'task': ['data-correction']}
| Provider | genai |
| Model | gemini-3.1-pro-preview |
| 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 | |||||
| 94.28 | 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 + 31.9K OT = 63.5K TT | Cost: 0.063$ + 0.383$ = 0.446$ |
{'document-type': ['newspaper-page'], 'century': [18], 'language': ['en'], 'task': ['data-correction']}
| Provider | genai |
| Model | gemini-3.1-flash-lite-preview |
| 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 | |||||
| 96.19 | 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 + 25.1K OT = 56.6K TT | Cost: 0.008$ + 0.038$ = 0.045$ |
{'document-type': ['newspaper-page'], 'century': [18], 'language': ['en'], 'task': ['data-correction']}
| Provider | openai |
| Model | gpt-5.4-2026-03-05 |
| 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 | |||||
| 96.78 | 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 + 26.2K OT = 59.8K TT | Cost: 0.084$ + 0.393$ = 0.477$ |
{'document-type': ['newspaper-page'], 'century': [18], 'language': ['en'], 'task': ['data-correction']}
| Provider | openai |
| Model | gpt-5.2-2025-12-11 |
| 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 | |||||
| 94.95 | 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: 33.7K IT + 28.4K OT = 62.0K TT | Cost: 0.059$ + 0.397$ = 0.456$ |
{'document-type': ['newspaper-page'], 'century': [18], 'language': ['en'], 'task': ['data-correction']}
| Provider | openai |
| Model | gpt-5-nano-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 | |||||
| 93.59 | 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 + 573.2K OT = 606.9K TT | Cost: 0.002$ + 0.229$ = 0.231$ |
{'document-type': ['newspaper-page'], 'century': [18], 'language': ['en'], 'task': ['data-correction']}
| Provider | openai |
| Model | o3-2025-04-16 |
| 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 | |||||
| 92.37 | 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 + 142.2K OT = 175.8K TT | Cost: 0.067$ + 1.138$ = 1.205$ |
{'document-type': ['newspaper-page'], 'century': [18], 'language': ['en'], 'task': ['data-correction']}
| Provider | openai |
| Model | gpt-5.1-2025-11-13 |
| 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 | |||||
| 95.15 | 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 + 37.8K OT = 71.5K TT | Cost: 0.042$ + 0.378$ = 0.420$ |