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': ['book-page'], 'writing': ['printed'], 'century': [20], 'language': ['en'], 'layout': ['list'], 'entry-type': ['bibliographic'], 'task': ['information-extraction']}
| Provider | genai |
| Model | gemini-3.1-flash-lite-preview |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 61.82 % |
| Test time | unknown seconds |
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 0.62 | 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: 5.8K IT + 9.7K OT = 15.5K TT | Cost: 0.001$ + 0.015$ = 0.016$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [20], 'language': ['en'], 'layout': ['list'], 'entry-type': ['bibliographic'], 'task': ['information-extraction']}
| Provider | genai |
| Model | gemini-3.1-pro-preview |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 60.27 % |
| Test time | unknown seconds |
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 0.60 | 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: 5.8K IT + 8.9K OT = 14.7K TT | Cost: 0.012$ + 0.106$ = 0.118$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [20], 'language': ['en'], 'layout': ['list'], 'entry-type': ['bibliographic'], 'task': ['information-extraction']}
| Provider | anthropic |
| Model | claude-opus-4-6 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 67.57 % |
| Test time | unknown seconds |
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 0.68 | 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: 16.2K IT + 8.8K OT = 25.0K TT | Cost: 0.081$ + 0.220$ = 0.301$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [20], 'language': ['en'], 'layout': ['list'], 'entry-type': ['bibliographic'], 'task': ['information-extraction']}
| Provider | anthropic |
| Model | claude-sonnet-4-6 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 67.52 % |
| Test time | unknown seconds |
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 0.68 | 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: 16.2K IT + 9.2K OT = 25.4K TT | Cost: 0.049$ + 0.138$ = 0.187$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [20], 'language': ['en'], 'layout': ['list'], 'entry-type': ['bibliographic'], 'task': ['information-extraction']}
| Provider | openai |
| Model | gpt-5.4-2026-03-05 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 69.83 % |
| Test time | unknown seconds |
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 0.70 | 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: 17.2K IT + 10.0K OT = 27.2K TT | Cost: 0.043$ + 0.150$ = 0.193$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [20], 'language': ['en'], 'layout': ['list'], 'entry-type': ['bibliographic'], 'task': ['information-extraction']}
| Provider | openai |
| Model | o3-2025-04-16 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 64.65 % |
| Test time | unknown seconds |
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 0.65 | 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: 8.2K IT + 18.7K OT = 26.9K TT | Cost: 0.016$ + 0.149$ = 0.166$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [20], 'language': ['en'], 'layout': ['list'], 'entry-type': ['bibliographic'], 'task': ['information-extraction']}
| Provider | openai |
| Model | gpt-5-2025-08-07 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 66.32 % |
| Test time | unknown seconds |
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 0.66 | 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: 7.9K IT + 31.6K OT = 39.5K TT | Cost: 0.010$ + 0.316$ = 0.326$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [20], 'language': ['en'], 'layout': ['list'], 'entry-type': ['bibliographic'], 'task': ['information-extraction']}
| Provider | openai |
| Model | gpt-5.1-2025-11-13 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 71.05 % |
| Test time | unknown seconds |
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 0.71 | 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: 7.9K IT + 10.2K OT = 18.1K TT | Cost: 0.010$ + 0.102$ = 0.112$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [20], 'language': ['en'], 'layout': ['list'], 'entry-type': ['bibliographic'], 'task': ['information-extraction']}
| Provider | openai |
| Model | gpt-5-mini-2025-08-07 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 67.67 % |
| Test time | unknown seconds |
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 0.68 | 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: 12.3K IT + 23.2K OT = 35.5K TT | Cost: 0.003$ + 0.046$ = 0.050$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [20], 'language': ['en'], 'layout': ['list'], 'entry-type': ['bibliographic'], 'task': ['information-extraction']}
| Provider | openai |
| Model | gpt-5-nano-2025-08-07 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 59.34 % |
| Test time | unknown seconds |
no valid result
| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| 0.59 | 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: 14.5K IT + 58.0K OT = 72.5K TT | Cost: 0.001$ + 0.023$ = 0.024$ |