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reasoning benchmark

Big Finance Bench

Big Finance Bench evaluates models on complex financial-analysis tasks that require retrieving and reasoning over financial documents and performing multi-step quantitative work.

Updated Aug 11, 2026

Models3
Model coverage3
MetricScore
EvidenceB

On this page

  • Ranking
  • Distribution
  • Highlights
  • About
  • FAQ

Big Finance Bench Ranking

Higher score ranks better on this benchmark.

3 rows
Columns

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1OPGPT-5.6 SolOpenAI53.0%100.0%3CAug 11, 2026
2OPGPT-5.6 TerraOpenAI51.0%50.0%3CAug 11, 2026
3OPGPT-5.6 LunaOpenAI36.0%0.0%3CAug 11, 2026

Big Finance Bench Score Distribution

A closer view of the leading scores on this benchmark.

Big Finance Bench

Big Finance Bench Highlights

The leading models and scores on this benchmark.

Rank #1GPT-5.6 Sol53.0%Rank #2GPT-5.6 Terra51.0%Rank #3GPT-5.6 Luna36.0%

What is Big Finance Bench?

What Big Finance Bench measures and how its scores work.

Big Finance Bench evaluates models on complex financial-analysis tasks that require retrieving and reasoning over financial documents and performing multi-step quantitative work.

Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.

Family
Big Finance Bench
Modality
text
Primary category
reasoning
Score direction
higher
LLMBoard eligible
Yes
Evaluation key
big-finance-bench|llm-stats-current

Benchmark scores retain their original unit. Overall score eligibility is shown separately.

FAQ

Common questions about Big Finance Bench.

Which model scores highest on Big Finance Bench?

GPT-5.6 Sol is currently ranked first with 53.0%.

What does Big Finance Bench measure?

Big Finance Bench evaluates models on complex financial-analysis tasks that require retrieving and reasoning over financial documents and performing multi-step quantitative work.

Is a higher score better?

Yes. Higher values rank better for this benchmark.

How many models are compared?

3 model results are currently shown.

Does this benchmark affect the overall score?

Yes. This benchmark can contribute to the current LLMBoard capability score.

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