Leaderboard

FinanceBench

Open-book questions about US public-company filings (10-Ks, 10-Qs, 8-Ks, earnings reports). The model must find and compute answers from the filing, usually through retrieval or long context.

Best reported

67

Numa 1Moneda

% correct, no filing given (150-question sample)

2 Nov 2026

Best value: Numa 1, 67 at $0.041 per question (cheapest within 5% of the top score)

FinanceBench: score vs cost

Score against cost per test. Up and to the left is better.

Updated 2 Nov 2026

Y: % correct, no filing given (150-question sample)X: Cost per test (USD)Showing 3 models
FinanceBench: score vs cost3 models. Frontier: Numa 1.60626466$0$0.05$0.1$0.15EfficientInefficient↑ Best performance← Lowest costCost per test (USD)Numa 1: 67 % correct, no filing given (150-question sample), $0.041 per test (API cost per question (model and search spend), measured in Moneda's run, 2 Nov 2026) Numa 1GPT-5.4: 63.7 % correct, no filing given (150-question sample), $0.044 per test (API cost per question (model and search spend), measured in Moneda's run, 2 Nov 2026) GPT-5.4Claude Opus 5.5: 60.3 % correct, no filing given (150-question sample), $0.156 per test (API cost per question (model and search spend), measured in Moneda's run, 2 Nov 2026)Claude Opus 5.5FinanceBench: score vs cost3 models. Frontier: Numa 1.60626466$0.05$0.1$0.2EfficientInefficient↑ Best performance← Lowest costCost per test (USD)Numa 1: 67 % correct, no filing given (150-question sample), $0.041 per test (API cost per question (model and search spend), measured in Moneda's run, 2 Nov 2026) Numa 1GPT-5.4: 63.7 % correct, no filing given (150-question sample), $0.044 per test (API cost per question (model and search spend), measured in Moneda's run, 2 Nov 2026) GPT-5.4Claude Opus 5.5: 60.3 % correct, no filing given (150-question sample), $0.156 per test (API cost per question (model and search spend), measured in Moneda's run, 2 Nov 2026)Claude Opus 5.5

FinanceBench arXiv v1 (2023-11-20); HF dataset last modified 2024-11-17

% correct, no filing given (150-question sample), higher is better. 5 models.

Updated 2 Nov 2026

  1. Numa 167
  2. GPT-5.463.7
  3. Claude Opus 5.560.3
  4. GPT-4-Turbo19
  5. Llama219

FinanceBench: cost

cost per test item (USD), lower is better. 3 models.

Updated 2 Nov 2026

  1. Numa 10.041
  2. GPT-5.40.044
  3. Claude Opus 5.50.156

FinanceBench arXiv v1 (2023-11-20); HF dataset last modified 2024-11-17

% correct, no filing given (150-question sample), higher is better. 5 models.

Updated 2 Nov 2026

  1. 1Numa 167
  2. 2GPT-5.463.7
  3. 3Claude Opus 5.560.3
  4. 4GPT-4-Turbo19
  5. 4Llama219
FinanceBench leaderboard (% correct, no filing given (150-question sample), higher is better)
1Numa 1Moneda67Finds its own filings, no documents given; graded by a two-judge panel (partly right counts half)Moneda run, 2026-11-02
Run by Moneda, 2 Nov 2026
2GPT-5.4OpenAI63.7Built-in web search, no documents given; same 150 questions and two-judge panel as Numa 1 (partly right counts half)Moneda run, 2026-11-02
Run by Moneda, 2 Nov 2026
3Claude Opus 5.5Anthropic60.3Built-in web search, no documents given; same 150 questions and two-judge panel as Numa 1 (partly right counts half)Moneda run, 2026-11-02
Run by Moneda, 2 Nov 2026
4GPT-4-TurboOpenAI19Shared vector store (all filings)Paper Table 2
Reported by the authors, 20 Nov 2023
4Llama2Meta19Shared vector store (all filings)Paper Table 2
Reported by the authors, 20 Nov 2023

FinanceBench arXiv v1 (2023-11-20); HF dataset last modified 2024-11-17

% correct, the right filing given (150-question sample), higher is better. 3 models.

Updated 20 Nov 2023

  1. GPT-4-Turbo85
  2. Claude276
  3. Llama241

FinanceBench arXiv v1 (2023-11-20); HF dataset last modified 2024-11-17

% correct, the right filing given (150-question sample), higher is better. 3 models.

Updated 20 Nov 2023

  1. 1GPT-4-Turbo85
  2. 2Claude276
  3. 3Llama241
FinanceBench leaderboard (% correct, the right filing given (150-question sample), higher is better)
1GPT-4-TurboOpenAI85Oracle (evidence pages given)Paper Table 2
Reported by the authors, 20 Nov 2023
2Claude2Anthropic76Long context (filing in context)Paper Table 2
Reported by the authors, 20 Nov 2023
3Llama2Meta41Single vector store (one per filing)Paper Table 2
Reported by the authors, 20 Nov 2023

Full details for FinanceBench