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': ['letter'], 'writing': ['typed', 'handwritten'], 'century': [20], 'language': ['de'], 'layout': ['prose'], 'entry-type': ['person', 'location'], 'task': ['information-extraction']}
| Provider | mistral |
| Model | ministral-14b-2512 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 0.00 % |
| Test time | unknown seconds |
IDENTITY and PURPOSE:
You are presented with a series of images constituting a historical letter. Your task is to extract the
values of the following keys from the letter and return them in a JSON file where the values
corresponding to each key should be stored as a list, even if there is only a single value for a
key:
- letter_title: Title of the letter.
- sender_persons: Name(s) of the person(s) who wrote the letter.
- send_date: The exact or approximate date the letter was written.
- receiver_persons: Name(s) of the person(s) who received the letter.
Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims
and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for
dates. If a piece of information is not included in the letter, set the value for the corresponding key
to "null". Do not return anything except the JSON file.
EXAMPLE:
{
"letter_title": ["Petition for Environmental Protection"],
"send_date": ["1993-03-12"],
"sender_persons": ["Lisa Simpson"],
"receiver_persons": ["Mayor Joe Quimby", "Seymour Skinner"],
}
OUTPUT:
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.00 | 0.00 | 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: 33.3K IT + 3.0K OT = 36.4K TT | Cost: 0.007$ + 0.001$ = 0.007$ |
{'document-type': ['letter'], 'writing': ['typed', 'handwritten'], 'century': [20], 'language': ['de'], 'layout': ['prose'], 'entry-type': ['person', 'location'], 'task': ['information-extraction']}
| Provider | anthropic |
| Model | claude-opus-4-5-20251101 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 58.00 % |
| Test time | unknown seconds |
IDENTITY and PURPOSE:
You are presented with a series of images constituting a historical letter. Your task is to extract the
values of the following keys from the letter and return them in a JSON file where the values
corresponding to each key should be stored as a list, even if there is only a single value for a
key:
- letter_title: Title of the letter.
- sender_persons: Name(s) of the person(s) who wrote the letter.
- send_date: The exact or approximate date the letter was written.
- receiver_persons: Name(s) of the person(s) who received the letter.
Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims
and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for
dates. If a piece of information is not included in the letter, set the value for the corresponding key
to "null". Do not return anything except the JSON file.
EXAMPLE:
{
"letter_title": ["Petition for Environmental Protection"],
"send_date": ["1993-03-12"],
"sender_persons": ["Lisa Simpson"],
"receiver_persons": ["Mayor Joe Quimby", "Seymour Skinner"],
}
OUTPUT:
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.59 | 0.58 | 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: 222.6K IT + 5.1K OT = 227.7K TT | Cost: 1.113$ + 0.128$ = 1.241$ |
{'document-type': ['letter'], 'writing': ['typed', 'handwritten'], 'century': [20], 'language': ['de'], 'layout': ['prose'], 'entry-type': ['person', 'location'], 'task': ['information-extraction']}
| Provider | anthropic |
| Model | claude-opus-4-5-20251101 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 53.00 % |
| Test time | unknown seconds |
IDENTITY and PURPOSE:
You are presented with a series of images constituting a historical letter. Your task is to extract the
values of the following keys from the letter and return them in a JSON file where the values
corresponding to each key should be stored as a list, even if there is only a single value for a
key:
- letter_title: Title of the letter.
- sender_persons: Name(s) of the person(s) who wrote the letter.
- send_date: The exact or approximate date the letter was written.
- receiver_persons: Name(s) of the person(s) who received the letter.
Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims
and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for
dates. If a piece of information is not included in the letter, set the value for the corresponding key
to "null". Do not return anything except the JSON file.
EXAMPLE:
{
"letter_title": ["Petition for Environmental Protection"],
"send_date": ["1993-03-12"],
"sender_persons": ["Lisa Simpson"],
"receiver_persons": ["Mayor Joe Quimby", "Seymour Skinner"],
}
OUTPUT:
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.62 | 0.53 | 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: 85.2K IT + 2.2K OT = 87.4K TT | Cost: 0.426$ + 0.055$ = 0.481$ |
{'document-type': ['letter'], 'writing': ['typed', 'handwritten'], 'century': [20], 'language': ['de'], 'layout': ['prose'], 'entry-type': ['person', 'location'], 'task': ['information-extraction']}
| Provider | openai |
| Model | gpt-4o-mini-2024-07-18 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 50.00 % |
| Test time | unknown seconds |
IDENTITY and PURPOSE:
You are presented with a series of images constituting a historical letter. Your task is to extract the
values of the following keys from the letter and return them in a JSON file where the values
corresponding to each key should be stored as a list, even if there is only a single value for a
key:
- letter_title: Title of the letter.
- sender_persons: Name(s) of the person(s) who wrote the letter.
- send_date: The exact or approximate date the letter was written.
- receiver_persons: Name(s) of the person(s) who received the letter.
Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims
and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for
dates. If a piece of information is not included in the letter, set the value for the corresponding key
to "null". Do not return anything except the JSON file.
EXAMPLE:
{
"letter_title": ["Petition for Environmental Protection"],
"send_date": ["1993-03-12"],
"sender_persons": ["Lisa Simpson"],
"receiver_persons": ["Mayor Joe Quimby", "Seymour Skinner"],
}
OUTPUT:
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.50 | 0.50 | 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: 3.6M IT + 3.9K OT = 3.6M TT | Cost: 0.546$ + 0.002$ = 0.548$ |
{'document-type': ['letter'], 'writing': ['typed', 'handwritten'], 'century': [20], 'language': ['de'], 'layout': ['prose'], 'entry-type': ['person', 'location'], 'task': ['information-extraction']}
| Provider | anthropic |
| Model | claude-opus-4-1-20250805 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 45.00 % |
| Test time | unknown seconds |
IDENTITY and PURPOSE:
You are presented with a series of images constituting a historical letter. Your task is to extract the
values of the following keys from the letter and return them in a JSON file where the values
corresponding to each key should be stored as a list, even if there is only a single value for a
key:
- letter_title: Title of the letter.
- sender_persons: Name(s) of the person(s) who wrote the letter.
- send_date: The exact or approximate date the letter was written.
- receiver_persons: Name(s) of the person(s) who received the letter.
Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims
and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for
dates. If a piece of information is not included in the letter, set the value for the corresponding key
to "null". Do not return anything except the JSON file.
EXAMPLE:
{
"letter_title": ["Petition for Environmental Protection"],
"send_date": ["1993-03-12"],
"sender_persons": ["Lisa Simpson"],
"receiver_persons": ["Mayor Joe Quimby", "Seymour Skinner"],
}
OUTPUT:
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.46 | 0.45 | 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: 207.0K IT + 6.1K OT = 213.1K TT | Cost: 3.105$ + 0.455$ = 3.561$ |
{'document-type': ['letter'], 'writing': ['typed', 'handwritten'], 'century': [20], 'language': ['de'], 'layout': ['prose'], 'entry-type': ['person', 'location'], 'task': ['information-extraction']}
| Provider | anthropic |
| Model | claude-opus-4-5-20251101 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 62.00 % |
| Test time | unknown seconds |
IDENTITY and PURPOSE:
You are presented with a series of images constituting a historical letter. Your task is to extract the
values of the following keys from the letter and return them in a JSON file where the values
corresponding to each key should be stored as a list, even if there is only a single value for a
key:
- letter_title: Title of the letter.
- sender_persons: Name(s) of the person(s) who wrote the letter.
- send_date: The exact or approximate date the letter was written.
- receiver_persons: Name(s) of the person(s) who received the letter.
Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims
and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for
dates. If a piece of information is not included in the letter, set the value for the corresponding key
to "null". Do not return anything except the JSON file.
EXAMPLE:
{
"letter_title": ["Petition for Environmental Protection"],
"send_date": ["1993-03-12"],
"sender_persons": ["Lisa Simpson"],
"receiver_persons": ["Mayor Joe Quimby", "Seymour Skinner"],
}
OUTPUT:
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.58 | 0.62 | 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: 137.4K IT + 2.9K OT = 140.3K TT | Cost: 0.687$ + 0.073$ = 0.760$ |
{'document-type': ['letter'], 'writing': ['typed', 'handwritten'], 'century': [20], 'language': ['de'], 'layout': ['prose'], 'entry-type': ['person', 'location'], 'task': ['information-extraction']}
| Provider | openai |
| Model | gpt-4.1-mini-2025-04-14 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 54.00 % |
| Test time | unknown seconds |
IDENTITY and PURPOSE:
You are presented with a series of images constituting a historical letter. Your task is to extract the
values of the following keys from the letter and return them in a JSON file where the values
corresponding to each key should be stored as a list, even if there is only a single value for a
key:
- letter_title: Title of the letter.
- sender_persons: Name(s) of the person(s) who wrote the letter.
- send_date: The exact or approximate date the letter was written.
- receiver_persons: Name(s) of the person(s) who received the letter.
Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims
and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for
dates. If a piece of information is not included in the letter, set the value for the corresponding key
to "null". Do not return anything except the JSON file.
EXAMPLE:
{
"letter_title": ["Petition for Environmental Protection"],
"send_date": ["1993-03-12"],
"sender_persons": ["Lisa Simpson"],
"receiver_persons": ["Mayor Joe Quimby", "Seymour Skinner"],
}
OUTPUT:
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.54 | 0.54 | 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: 261.7K IT + 3.1K OT = 264.8K TT | Cost: 0.105$ + 0.005$ = 0.110$ |
{'document-type': ['letter'], 'writing': ['typed', 'handwritten'], 'century': [20], 'language': ['de'], 'layout': ['prose'], 'entry-type': ['person', 'location'], 'task': ['information-extraction']}
| Provider | openai |
| Model | gpt-4.1-2025-04-14 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 58.00 % |
| Test time | unknown seconds |
IDENTITY and PURPOSE:
You are presented with a series of images constituting a historical letter. Your task is to extract the
values of the following keys from the letter and return them in a JSON file where the values
corresponding to each key should be stored as a list, even if there is only a single value for a
key:
- letter_title: Title of the letter.
- sender_persons: Name(s) of the person(s) who wrote the letter.
- send_date: The exact or approximate date the letter was written.
- receiver_persons: Name(s) of the person(s) who received the letter.
Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims
and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for
dates. If a piece of information is not included in the letter, set the value for the corresponding key
to "null". Do not return anything except the JSON file.
EXAMPLE:
{
"letter_title": ["Petition for Environmental Protection"],
"send_date": ["1993-03-12"],
"sender_persons": ["Lisa Simpson"],
"receiver_persons": ["Mayor Joe Quimby", "Seymour Skinner"],
}
OUTPUT:
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.53 | 0.58 | 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: 85.3K IT + 2.1K OT = 87.3K TT | Cost: 0.171$ + 0.016$ = 0.187$ |
{'document-type': ['letter'], 'writing': ['typed', 'handwritten'], 'century': [20], 'language': ['de'], 'layout': ['prose'], 'entry-type': ['person', 'location'], 'task': ['information-extraction']}
| Provider | anthropic |
| Model | claude-sonnet-4-5-20250929 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 46.00 % |
| Test time | unknown seconds |
IDENTITY and PURPOSE:
You are presented with a series of images constituting a historical letter. Your task is to extract the
values of the following keys from the letter and return them in a JSON file where the values
corresponding to each key should be stored as a list, even if there is only a single value for a
key:
- letter_title: Title of the letter.
- sender_persons: Name(s) of the person(s) who wrote the letter.
- send_date: The exact or approximate date the letter was written.
- receiver_persons: Name(s) of the person(s) who received the letter.
Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims
and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for
dates. If a piece of information is not included in the letter, set the value for the corresponding key
to "null". Do not return anything except the JSON file.
EXAMPLE:
{
"letter_title": ["Petition for Environmental Protection"],
"send_date": ["1993-03-12"],
"sender_persons": ["Lisa Simpson"],
"receiver_persons": ["Mayor Joe Quimby", "Seymour Skinner"],
}
OUTPUT:
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.47 | 0.46 | 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: 222.6K IT + 5.8K OT = 228.3K TT | Cost: 0.668$ + 0.086$ = 0.754$ |
{'document-type': ['letter'], 'writing': ['typed', 'handwritten'], 'century': [20], 'language': ['de'], 'layout': ['prose'], 'entry-type': ['person', 'location'], 'task': ['information-extraction']}
| Provider | openai |
| Model | gpt-4.1-nano-2025-04-14 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 46.00 % |
| Test time | unknown seconds |
IDENTITY and PURPOSE:
You are presented with a series of images constituting a historical letter. Your task is to extract the
values of the following keys from the letter and return them in a JSON file where the values
corresponding to each key should be stored as a list, even if there is only a single value for a
key:
- letter_title: Title of the letter.
- sender_persons: Name(s) of the person(s) who wrote the letter.
- send_date: The exact or approximate date the letter was written.
- receiver_persons: Name(s) of the person(s) who received the letter.
Take a deep breath and think step by step about how to best accomplish this goal. Map out all the claims
and implications on a virtual whiteboard in your mind. Do not use OCR. Use the ISO format YYYY-MM-DD for
dates. If a piece of information is not included in the letter, set the value for the corresponding key
to "null". Do not return anything except the JSON file.
EXAMPLE:
{
"letter_title": ["Petition for Environmental Protection"],
"send_date": ["1993-03-12"],
"sender_persons": ["Lisa Simpson"],
"receiver_persons": ["Mayor Joe Quimby", "Seymour Skinner"],
}
OUTPUT:
no valid result| Fuzzy Score | F1 micro / macro | Micro precision/recall | Tue/False Positives | |||||
| n/a | 0.47 | 0.46 | 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: 382.9K IT + 3.2K OT = 386.1K TT | Cost: 0.038$ + 0.001$ = 0.040$ |