Prompt: Table understanding
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How models perform on this prompt
Arcee.ai Spotlight
Model answer: The adjusted EBITDA for the nine months ended September 30, 2023, is $2,428 million.
Claude 3.5 Haiku
Model answer: According to the financial table, the Adjusted EBITDA for the nine months ended September 30, 2023 is $2,428 thousand, which is equivalent to $2.428 million.
Claude 3.7 Sonnet
Model answer: Based on the financial table, the adjusted EBITDA for the nine months ended September 30, 2023 was $2.428 million (or $2,428 thousand as shown in the table). This represents a significant improvement compared to 2024, where the nine-month adjusted EBITDA was $232.598 million. The percent change is marked as "NM" (Not Meaningful) due to the extremely large percentage increase from 2023 to 2024.
Claude 4 Opus
Model answer: According to the table, the Adjusted EBITDA for the nine months ended September 30, 2023 was $2,428 thousand, which equals $2.428 million.
Claude 4 Sonnet
Model answer: According to the table, the Adjusted EBITDA for the nine months ended September 30, 2023 was $2,428 thousand. Converting to millions: $2,428 thousand = $2.428 million (or approximately $2.4 million).
Claude 4.1 Opus
Model answer: According to the table, the Adjusted EBITDA for the nine months ended September 30, 2023 was $2,428 thousand, which equals approximately $2.4 million.
GPT-4.1
Model answer: { "answer": "2,428" }
GPT-5
Model answer: {"answer": "2.428"}
GPT-5 (high reasoning)
Model answer: {"answer": "2.428"}
GPT-5 Nano
Model answer: {"answer": "2.428"}
GPT-5.1
Model answer: {"answer": "2.428"}
GPT-5.2
Model answer: {"answer":"2.428"}
Gemini 2.0 Flash
Model answer: {"answer": "2.428"}
Gemini 2.5 Flash
Model answer: {"answer": "2.428"}
Gemini 2.5 Pro
Model answer: { "answer": 2.428 }
Gemini 3 Flash
Model answer: { "answer": "2.428" }
Gemini 3 Flash (Tools)
Model answer: {"answer": "2.428"}
Gemini 3 Pro Preview
Model answer: {"answer": "2.428"}
Gemma 3 27b
Model answer: According to the provided text, the adjusted EBITDA for the nine months ended September 2023 was **$2,428 million**.
Llama 4 Maverick 17B
Model answer: To find the adjusted EBITDA for the nine months ended September 2023, we need to look at the "Nine Months Ended September 30" column in the table. The adjusted EBITDA for the nine months ended September 2023 is $2,428 thousand. To convert this to millions, we divide by 1,000 since there are 1,000 thousands in a million. $2,428 / 1,000 = $2.428 million. Therefore, the adjusted EBITDA in the nine months ended September 2023 was $2.428 million.
Llama 4 Scout 17B
Model answer: The adjusted EBITDA for the nine months ended September 2023 is $2,428 million. To find this answer, locate the "Adjusted EBITDA" row and move to the right to find the column "Nine Months Ended September 30, 2023". The value is $2,428. Note that the unit is in thousands, but the question asks for millions. To convert it to millions, divide by 1,000. $2,428 (in thousands) = $2.428 million. However, the ground truth answer is 2428 which implies that the unit for the ground truth answer is actually in thousands and it was directly taken from the table without conversion. Therefore, to be consistent with the ground truth answer, we keep it as $2,428. To express it in millions we can write it as $2.428 million.
Mistral Medium 3
Model answer: The adjusted EBITDA for the nine months ended September 30, 2023, is directly provided in the table under the relevant column. Here are the details: - Adjusted EBITDA for the nine months ended September 30, 2023: $2,428 (in thousands) - Conversion to millions: $2,428 / 1,000 = $2.428 million After verifying the data from the table, the adjusted EBITDA is indeed $2,428 in thousands. So, the final answer is **2.428 million**.
Mistral Small 3.1 24B
Model answer: To determine the adjusted EBITDA for the nine months ended September 2023, we need to look at the provided table. The table shows financial data for both three months and nine months ended September 2023 and September 2024. Here's the relevant information: - The table provides the adjusted EBITDA for three months and nine months ended September 2023 and September 2024. - For the nine months ended September 2023, the adjusted EBITDA is listed as $2,428 million. By examining the table, we see: - **Nine Months Ended September 30, 2023 (Adjusted EBITDA)**: $2,428 million Thus, the **adjusted EBITDA for the nine months ended September 2023 is $2,428 million**.
OpenAI O3 (High Reasoning)
Model answer: {"answer": "2.428"}
OpenAI O4 Mini (Medium Reasoning)
Model answer: {"answer": "2.428"}
Phi 4 Multimodal
Model answer: $2,428 million.
Qwen 2.5 VL 7B
Model answer: The adjusted EBITDA for the nine months ended September 30, 2023, is $2,428 million.
ChatGPT-4o (High Reasoning)
Model answer: { "answer": "232.598" }
ChatGPT-4o (Medium Reasoning)
Model answer: { "answer": "232.598" }
Claude 4.6 Opus
Model answer: {"answer": "$2.428 million"}
Cohere Aya Vision 32B
Model answer: The adjusted EBITDA in the nine months ended September 2023 was $40,094 million. This figure represents a 229% increase compared to the same period in the prior year, which was $12,781 million. The adjusted EBITDA is calculated by adding back certain non-cash and non-operating items to the net income, providing a clearer picture of the company's operational performance. In this case, the significant increase in adjusted EBITDA highlights improved operational efficiency and profitability over the prior year.
Cohere Aya Vision 8B
Model answer: The adjusted EBITDA for the nine months ended September 30, 2023, is $131,962 million. This figure represents a 40% increase compared to the same period in the previous year.
GPT-4.1 Mini
Model answer: {"answer": "232.598"}
GPT-4.1 Nano
Model answer: {"answer": "232.598"}
GPT-5 Mini
Model answer: {"answer": "$2.428 million"}
Gemini 2.0 Flash Lite
Model answer: { "answer": "232598" }
Gemini 2.5 Flash Lite
Model answer: {"answer": "232,598"}
Gemma 3 4B
Model answer: According to the table, the adjusted EBITDA for the nine months ended September 2023 is **$232,598 million**.
OpenAI O1
Model answer: {"answer": "2.4"}
OpenAI O3 (Medium Reasoning)
Model answer: {"answer": "about $2.4 million"}
OpenAI O4 Mini (High Reasoning)
Model answer: {"answer":"$2.428 million"}