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 | scicore |
| Model | qwen35-397b-a17b-fp8 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 55.00 % |
| 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 | 0.55 | 0.55 | 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: 302.5K IT + 322.7K OT = 625.2K TT | Cost: 0.000$ + 0.000$ = 0.000$ |
{'document-type': ['letter'], 'writing': ['typed', 'handwritten'], 'century': [20], 'language': ['de'], 'layout': ['prose'], 'entry-type': ['person', 'location'], 'task': ['information-extraction']}
| Provider | scicore |
| Model | qwen35-397b-a17b-fp8 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 52.00 % |
| 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 | 0.60 | 0.52 | 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: 109.5K IT + 126.3K OT = 235.8K TT | Cost: 0.000$ + 0.000$ = 0.000$ |
{'document-type': ['letter'], 'writing': ['typed', 'handwritten'], 'century': [20], 'language': ['de'], 'layout': ['prose'], 'entry-type': ['person', 'location'], 'task': ['information-extraction']}
| Provider | scicore |
| Model | qwen35-397b-a17b-fp8 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 57.00 % |
| 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 | 0.52 | 0.57 | 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: 192.6K IT + 196.4K OT = 389.0K TT | Cost: 0.000$ + 0.000$ = 0.000$ |
{'document-type': ['letter'], 'writing': ['typed', 'handwritten'], 'century': [20], 'language': ['de'], 'layout': ['prose'], 'entry-type': ['person', 'location'], 'task': ['information-extraction']}
| Provider | x-ai |
| Model | grok-4.3 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 74.00 % |
| 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 | 0.83 | 0.74 | 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: 99.0K IT + 1.2K OT = 100.3K TT | Cost: 0.124$ + 0.003$ = 0.127$ |
{'document-type': ['letter'], 'writing': ['typed', 'handwritten'], 'century': [20], 'language': ['de'], 'layout': ['prose'], 'entry-type': ['person', 'location'], 'task': ['information-extraction']}
| Provider | x-ai |
| Model | grok-4.3 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 64.00 % |
| 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 | 0.65 | 0.64 | 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: 269.2K IT + 3.0K OT = 272.2K TT | Cost: 0.336$ + 0.008$ = 0.344$ |
{'document-type': ['letter'], 'writing': ['typed', 'handwritten'], 'century': [20], 'language': ['de'], 'layout': ['prose'], 'entry-type': ['person', 'location'], 'task': ['information-extraction']}
| Provider | x-ai |
| Model | grok-4.3 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 67.00 % |
| 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 | 0.67 | 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: 170.1K IT + 1.8K OT = 171.9K TT | Cost: 0.213$ + 0.004$ = 0.217$ |
{'document-type': ['letter'], 'writing': ['typed', 'handwritten'], 'century': [20], 'language': ['de'], 'layout': ['prose'], 'entry-type': ['person', 'location'], 'task': ['information-extraction']}
| Provider | openrouter |
| Model | meta-llama/llama-4-scout-17b-16e-instruct |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 51.00 % |
| 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 | 0.52 | 0.51 | 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: 229.9K IT + 3.6K OT = 233.5K TT | Cost: 0.018$ + 0.001$ = 0.019$ |
{'document-type': ['letter'], 'writing': ['typed', 'handwritten'], 'century': [20], 'language': ['de'], 'layout': ['prose'], 'entry-type': ['person', 'location'], 'task': ['information-extraction']}
| Provider | openrouter |
| Model | stepfun/step-3.7-flash-20260528 |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 55.00 % |
| 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 | 0.55 | 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: 84.9K IT + 104.4K OT = 189.3K TT | Cost: 0.017$ + 0.120$ = 0.137$ |
{'document-type': ['letter'], 'writing': ['typed', 'handwritten'], 'century': [20], 'language': ['de'], 'layout': ['prose'], 'entry-type': ['person', 'location'], 'task': ['information-extraction']}
| Provider | openrouter |
| Model | meta-llama/llama-4-scout-17b-16e-instruct |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 48.00 % |
| 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 | 0.48 | 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: 82.2K IT + 1.5K OT = 83.8K TT | Cost: 0.007$ + 0.000$ = 0.007$ |
{'document-type': ['letter'], 'writing': ['typed', 'handwritten'], 'century': [20], 'language': ['de'], 'layout': ['prose'], 'entry-type': ['person', 'location'], 'task': ['information-extraction']}
| Provider | openrouter |
| Model | meta-llama/llama-4-scout-17b-16e-instruct |
| Temperature | 0.0 |
| Dataclass | Document |
| Normalized Score | 55.00 % |
| 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 | 0.51 | 0.55 | 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: 157.8K IT + 2.3K OT = 160.1K TT | Cost: 0.013$ + 0.001$ = 0.013$ |