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', 'de'], 'layout': ['list'], 'entry-type': ['company'], 'task': ['information-extraction']}
| Provider | anthropic |
| Model | claude-opus-4-1-20250805 |
| Temperature | 0.5 |
| Dataclass | ListPage |
| Normalized Score | 45.20 % |
| Test time | unknown seconds |
The image you are presented with stems from a digitized book containing lists of companies.
Your task is to extract structured information about each company listed on the page.
About the source:
- The image stems from a trade index of the British Swiss Chamber of Commerce.
- The image can show an alphabetical or a thematic list of companies.
- The companies are mostly located in Switzerland and the UK.
- The image stems from a trade index between 1925 and 1958.
- Most pages have one column but some years have two columns.
- The source itself is in English and German but the company names can be in English, German, French or Italian.
About the entries:
- Each entry describes a single company or person.
- Alphabetical entries have filling dots between the company name and the page number. Dots and page numbers are not part of the data and should be ignored.
- Alphabetical entries seldom to never have locations.
- Thematic entries often have locations.
- Thematic entries are listed under headings that describe the type of business.
- Some thematic headings are only references to other headings, e.g. "X, s. Y".
About the output:
- Answer in valid JSON. The JSON should be an array of objects with the following fields:
- The page ID is given as {page_id}.
- Do not add country information, if it is not directly written with the location.
{
"entry_id": "A unique identifier for the entry, e.g. '{page_id}-1'",
"company_name": "The name of the company or person",
"location": "The location of the company, e.g. 'Zurich' or 'London, UK'. If no location is given, set to null."
]
}
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.45 | 0.45 | 0.45 | 0.45 | 15 | 445 | 550 | 547 |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: 7 months ago, 2025-10-28. | Tokens: 28.0K IT + 17.1K OT = 45.1K TT | Cost: 0.421$ + 1.279$ = 1.699$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [20], 'language': ['en', 'de'], 'layout': ['list'], 'entry-type': ['company'], 'task': ['information-extraction']}
| Provider | mistral |
| Model | mistral-large-latest |
| Temperature | 0.5 |
| Dataclass | ListPage |
| Normalized Score | 43.73 % |
| Test time | unknown seconds |
The image you are presented with stems from a digitized book containing lists of companies.
Your task is to extract structured information about each company listed on the page.
About the source:
- The image stems from a trade index of the British Swiss Chamber of Commerce.
- The image can show an alphabetical or a thematic list of companies.
- The companies are mostly located in Switzerland and the UK.
- The image stems from a trade index between 1925 and 1958.
- Most pages have one column but some years have two columns.
- The source itself is in English and German but the company names can be in English, German, French or Italian.
About the entries:
- Each entry describes a single company or person.
- Alphabetical entries have filling dots between the company name and the page number. Dots and page numbers are not part of the data and should be ignored.
- Alphabetical entries seldom to never have locations.
- Thematic entries often have locations.
- Thematic entries are listed under headings that describe the type of business.
- Some thematic headings are only references to other headings, e.g. "X, s. Y".
About the output:
- Answer in valid JSON. The JSON should be an array of objects with the following fields:
- The page ID is given as {page_id}.
- Do not add country information, if it is not directly written with the location.
{
"entry_id": "A unique identifier for the entry, e.g. '{page_id}-1'",
"company_name": "The name of the company or person",
"location": "The location of the company, e.g. 'Zurich' or 'London, UK'. If no location is given, set to null."
]
}
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.44 | 0.44 | 0.44 | 0.44 | 15 | 434 | 556 | 558 |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: 7 months ago, 2025-10-28. | Tokens: 22.6K IT + 14.2K OT = 36.8K TT | Cost: 0.045$ + 0.085$ = 0.130$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [20], 'language': ['en', 'de'], 'layout': ['list'], 'entry-type': ['company'], 'task': ['information-extraction']}
| Provider | anthropic |
| Model | claude-opus-4-20250514 |
| Temperature | 0.5 |
| Dataclass | ListPage |
| Normalized Score | 49.33 % |
| Test time | unknown seconds |
The image you are presented with stems from a digitized book containing lists of companies.
Your task is to extract structured information about each company listed on the page.
About the source:
- The image stems from a trade index of the British Swiss Chamber of Commerce.
- The image can show an alphabetical or a thematic list of companies.
- The companies are mostly located in Switzerland and the UK.
- The image stems from a trade index between 1925 and 1958.
- Most pages have one column but some years have two columns.
- The source itself is in English and German but the company names can be in English, German, French or Italian.
About the entries:
- Each entry describes a single company or person.
- Alphabetical entries have filling dots between the company name and the page number. Dots and page numbers are not part of the data and should be ignored.
- Alphabetical entries seldom to never have locations.
- Thematic entries often have locations.
- Thematic entries are listed under headings that describe the type of business.
- Some thematic headings are only references to other headings, e.g. "X, s. Y".
About the output:
- Answer in valid JSON. The JSON should be an array of objects with the following fields:
- The page ID is given as {page_id}.
- Do not add country information, if it is not directly written with the location.
{
"entry_id": "A unique identifier for the entry, e.g. '{page_id}-1'",
"company_name": "The name of the company or person",
"location": "The location of the company, e.g. 'Zurich' or 'London, UK'. If no location is given, set to null."
]
}
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.50 | 0.49 | 0.50 | 0.50 | 15 | 495 | 502 | 497 |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: 7 months ago, 2025-10-28. | Tokens: 28.0K IT + 17.0K OT = 45.0K TT | Cost: 0.421$ + 1.275$ = 1.695$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [20], 'language': ['en', 'de'], 'layout': ['list'], 'entry-type': ['company'], 'task': ['information-extraction']}
| Provider | openai |
| Model | gpt-5-nano |
| Temperature | 0.5 |
| Dataclass | ListPage |
| Normalized Score | 26.13 % |
| Test time | unknown seconds |
- Answer in valid JSON.
- The page ID is given as {page_id}.
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.27 | 0.26 | 0.32 | 0.24 | 15 | 235 | 503 | 757 |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: 7 months ago, 2025-10-28. | Tokens: 18.0K IT + 66.3K OT = 84.4K TT | Cost: 0.001$ + 0.027$ = 0.027$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [20], 'language': ['en', 'de'], 'layout': ['list'], 'entry-type': ['company'], 'task': ['information-extraction']}
| Provider | scicore |
| Model | GLM-4.5V-FP8 |
| Temperature | 0.5 |
| Dataclass | ListPage |
| Normalized Score | 0.00 % |
| Test time | unknown seconds |
- Answer in valid JSON.
- The page ID is given as {page_id}.
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.00 | 0.00 | 0.00 | 0.00 | 15 | 0 | 15 | 992 |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: 7 months ago, 2025-10-28. | Tokens: 0 IT + 0 OT = 0 TT | Cost: 0.000$ + 0.000$ = 0.000$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [20], 'language': ['en', 'de'], 'layout': ['list'], 'entry-type': ['company'], 'task': ['information-extraction']}
| Provider | genai |
| Model | gemini-2.5-flash-lite |
| Temperature | 0.5 |
| Dataclass | ListPage |
| Normalized Score | 30.60 % |
| Test time | unknown seconds |
- Answer in valid JSON.
- The page ID is given as {page_id}.
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.27 | 0.31 | 0.26 | 0.29 | 15 | 284 | 793 | 708 |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: 7 months ago, 2025-10-28. | Tokens: 4.2K IT + 16.9K OT = 21.1K TT | Cost: 0.000$ + 0.007$ = 0.007$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [20], 'language': ['en', 'de'], 'layout': ['list'], 'entry-type': ['company'], 'task': ['information-extraction']}
| Provider | anthropic |
| Model | claude-sonnet-4-5-20250929 |
| Temperature | 0.5 |
| Dataclass | ListPage |
| Normalized Score | 41.20 % |
| Test time | unknown seconds |
The image you are presented with stems from a digitized book containing lists of companies.
Your task is to extract structured information about each company listed on the page.
About the source:
- The image stems from a trade index of the British Swiss Chamber of Commerce.
- The image can show an alphabetical or a thematic list of companies.
- The companies are mostly located in Switzerland and the UK.
- The image stems from a trade index between 1925 and 1958.
- Most pages have one column but some years have two columns.
- The source itself is in English and German but the company names can be in English, German, French or Italian.
About the entries:
- Each entry describes a single company or person.
- Alphabetical entries have filling dots between the company name and the page number. Dots and page numbers are not part of the data and should be ignored.
- Alphabetical entries seldom to never have locations.
- Thematic entries often have locations.
- Thematic entries are listed under headings that describe the type of business.
- Some thematic headings are only references to other headings, e.g. "X, s. Y".
About the output:
- Answer in valid JSON. The JSON should be an array of objects with the following fields:
- The page ID is given as {page_id}.
- Do not add country information, if it is not directly written with the location.
{
"entry_id": "A unique identifier for the entry, e.g. '{page_id}-1'",
"company_name": "The name of the company or person",
"location": "The location of the company, e.g. 'Zurich' or 'London, UK'. If no location is given, set to null."
]
}
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.41 | 0.41 | 0.41 | 0.41 | 15 | 410 | 578 | 582 |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: 7 months ago, 2025-10-28. | Tokens: 32.1K IT + 18.1K OT = 50.2K TT | Cost: 0.096$ + 0.272$ = 0.368$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [20], 'language': ['en', 'de'], 'layout': ['list'], 'entry-type': ['company'], 'task': ['information-extraction']}
| Provider | mistral |
| Model | pixtral-large-latest |
| Temperature | 0.5 |
| Dataclass | ListPage |
| Normalized Score | 30.40 % |
| Test time | unknown seconds |
- Answer in valid JSON.
- The page ID is given as {page_id}.
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.32 | 0.30 | 0.31 | 0.32 | 15 | 315 | 688 | 677 |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: 7 months ago, 2025-10-28. | Tokens: 45.6K IT + 21.3K OT = 66.8K TT | Cost: 0.091$ + 0.128$ = 0.219$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [20], 'language': ['en', 'de'], 'layout': ['list'], 'entry-type': ['company'], 'task': ['information-extraction']}
| Provider | mistral |
| Model | mistral-medium-2505 |
| Temperature | 0.5 |
| Dataclass | ListPage |
| Normalized Score | 38.93 % |
| Test time | unknown seconds |
- Answer in valid JSON.
- The page ID is given as {page_id}.
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.36 | 0.39 | 0.38 | 0.34 | 15 | 336 | 537 | 656 |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: 7 months ago, 2025-10-28. | Tokens: 16.2K IT + 11.8K OT = 27.9K TT | Cost: 0.006$ + 0.024$ = 0.030$ |
{'document-type': ['book-page'], 'writing': ['printed'], 'century': [20], 'language': ['en', 'de'], 'layout': ['list'], 'entry-type': ['company'], 'task': ['information-extraction']}
| Provider | anthropic |
| Model | claude-opus-4-1-20250805 |
| Temperature | 0.5 |
| Dataclass | ListPage |
| Normalized Score | 45.87 % |
| Test time | unknown seconds |
- Answer in valid JSON.
- The page ID is given as {page_id}.
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.45 | 0.46 | 0.44 | 0.47 | 15 | 467 | 601 | 525 |
| Micro Precision | Micro Recall | Instances | TP | FP | FN | |||
| Pricing Date: 7 months ago, 2025-10-28. | Tokens: 22.3K IT + 16.9K OT = 39.2K TT | Cost: 0.334$ + 1.268$ = 1.602$ |