# Best AI for Financial filings Q&A (November 2026) The leader on each benchmark in this use case, never combined. Data refreshed 2 Nov 2026. ## Picks - CorpFin v2: Claude Opus 5: 73.2 accuracy % (Vals.ai leaderboard (archived), 12 Aug 2026), https://benchmarks.finance/leaderboards/vals-corpfin-v2/ - IPO Finance Agent: GLM-5.2: 79.8 mean rubric score % (Paper Table 1, 30 Jun 2026), https://benchmarks.finance/leaderboards/ipo-finance-agent/ - FinanceBench: Numa 1: 67 % correct, no filing given (150-question sample) (Moneda run, 2026-11-02, 2 Nov 2026), https://benchmarks.finance/leaderboards/financebench/ - FinanceQA: o1: 0.487 accuracy (total, 0-1) (Paper Table 1, 30 Jan 2025), https://benchmarks.finance/leaderboards/afterquery-financeqa/ - MortgageTax: Claude Opus 5: 72.1 accuracy % (Vals.ai MortgageTax leaderboard, 1 Sept 2026), https://benchmarks.finance/leaderboards/vals-mortgage-tax/ - Moneda FilingsBench: Numa 1: 91.6 % correct (private split) (Moneda run, 2026-11-02, 2 Nov 2026), https://benchmarks.finance/leaderboards/moneda-filingsbench/ ## CorpFin v2: accuracy % (higher is better, 10 models) | Rank | Model | Provider | Score | Metric | Setting | Reported by | Source | URL | Date | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 1 | Claude Opus 5 | Anthropic | 73.2 | accuracy % | | Official board | Vals.ai leaderboard (archived) | https://www.vals.ai/benchmarks/corp_fin_v2 | 12 Aug 2026 (checked 1 Nov 2026) | | 2 | Claude Fable 5 | Anthropic | 71.8 | accuracy % | | Official board | Vals.ai leaderboard (archived) | https://www.vals.ai/benchmarks/corp_fin_v2 | 12 Aug 2026 (checked 1 Nov 2026) | | 3 | Kimi K3 | Moonshot AI | 71.6 | accuracy % | | Official board | Vals.ai leaderboard (archived) | https://www.vals.ai/benchmarks/corp_fin_v2 | 12 Aug 2026 (checked 1 Nov 2026) | | 4 | Muse Spark 1.1 | Meta | 71.3 | accuracy % | | Official board | Vals.ai leaderboard (archived) | https://www.vals.ai/benchmarks/corp_fin_v2 | 12 Aug 2026 (checked 1 Nov 2026) | | 5 | Muse Spark 1.2 | Meta | 70.9 | accuracy % | | Official board | Vals.ai leaderboard (archived) | https://www.vals.ai/benchmarks/corp_fin_v2 | 12 Aug 2026 (checked 1 Nov 2026) | | 6 | Inkling Small | Not stated | 69.6 | accuracy % | | Official board | Vals.ai leaderboard (archived) | https://www.vals.ai/benchmarks/corp_fin_v2 | 12 Aug 2026 (checked 1 Nov 2026) | | 7 | Inkling | Not stated | 68.6 | accuracy % | | Official board | Vals.ai leaderboard (archived) | https://www.vals.ai/benchmarks/corp_fin_v2 | 12 Aug 2026 (checked 1 Nov 2026) | | 8 | Grok 4.3 | xAI | 68.5 | accuracy % | | Official board | Vals.ai leaderboard (archived) | https://www.vals.ai/benchmarks/corp_fin_v2 | 12 Aug 2026 (checked 1 Nov 2026) | | 9 | GPT-5.5 | OpenAI | 68.4 | accuracy % | | Official board | Vals.ai leaderboard (archived) | https://www.vals.ai/benchmarks/corp_fin_v2 | 12 Aug 2026 (checked 1 Nov 2026) | | 10 | Kimi K2.5 | Moonshot AI | 68.3 | accuracy % | | Official board | Vals.ai leaderboard (archived) | https://www.vals.ai/benchmarks/corp_fin_v2 | 12 Aug 2026 (checked 1 Nov 2026) | ## IPO Finance Agent: mean rubric score % (higher is better, 6 models) | Rank | Model | Provider | Score | Metric | Setting | Reported by | Source | URL | Date | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 1 | GLM-5.2 | Zhipu AI | 79.8 | mean rubric score % | public SpaceX set (n=70), agent harness | Reported by the authors | Paper Table 1 | https://arxiv.org/html/2606.23032v3 | 30 Jun 2026 (checked 1 Nov 2026) | | 2 | GLM-5.1 | Zhipu AI | 79.7 | mean rubric score % | public SpaceX set (n=70), agent harness | Reported by the authors | Paper Table 1 | https://arxiv.org/html/2606.23032v3 | 30 Jun 2026 (checked 1 Nov 2026) | | 3 | Qwen3.7-Max | Qwen | 78.9 | mean rubric score % | public SpaceX set (n=70), agent harness | Reported by the authors | Paper Table 1 | https://arxiv.org/html/2606.23032v3 | 30 Jun 2026 (checked 1 Nov 2026) | | 4 | MiMo-2.5 Pro | Xiaomi | 77.2 | mean rubric score % | public SpaceX set (n=70), agent harness | Reported by the authors | Paper Table 1 | https://arxiv.org/html/2606.23032v3 | 30 Jun 2026 (checked 1 Nov 2026) | | 5 | Kimi K2.6 | Moonshot AI | 68 | mean rubric score % | public SpaceX set (n=70), agent harness | Reported by the authors | Paper Table 1 | https://arxiv.org/html/2606.23032v3 | 30 Jun 2026 (checked 1 Nov 2026) | | 6 | Nemotron 3 Ultra | NVIDIA | 45.5 | mean rubric score % | public SpaceX set (n=70), agent harness | Reported by the authors | Paper Table 1 | https://arxiv.org/html/2606.23032v3 | 30 Jun 2026 (checked 1 Nov 2026) | ## FinanceBench: % correct, no filing given (150-question sample) (higher is better, 5 models) | Rank | Model | Provider | Score | Metric | Setting | Reported by | Source | URL | Date | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 1 | Numa 1 | Moneda | 67 | % correct, no filing given (150-question sample) | Finds its own filings, no documents given; graded by a two-judge panel (partly right counts half) | Run by Moneda | Moneda run, 2026-11-02 | https://benchmarks.finance/method/ | 2 Nov 2026 | | 2 | GPT-5.4 | OpenAI | 63.7 | % correct, no filing given (150-question sample) | Built-in web search, no documents given; same 150 questions and two-judge panel as Numa 1 (partly right counts half) | Run by Moneda | Moneda run, 2026-11-02 | https://benchmarks.finance/method/ | 2 Nov 2026 | | 3 | Claude Opus 5.5 | Anthropic | 60.3 | % correct, no filing given (150-question sample) | Built-in web search, no documents given; same 150 questions and two-judge panel as Numa 1 (partly right counts half) | Run by Moneda | Moneda run, 2026-11-02 | https://benchmarks.finance/method/ | 2 Nov 2026 | | 4 | GPT-4-Turbo | OpenAI | 19 | % correct, no filing given (150-question sample) | Shared vector store (all filings) | Reported by the authors | Paper Table 2 | https://arxiv.org/html/2311.11944v1 | 20 Nov 2023 (checked 2 Nov 2026) | | 4 | Llama2 | Meta | 19 | % correct, no filing given (150-question sample) | Shared vector store (all filings) | Reported by the authors | Paper Table 2 | https://arxiv.org/html/2311.11944v1 | 20 Nov 2023 (checked 2 Nov 2026) | ## FinanceQA: accuracy (total, 0-1) (higher is better, 5 models) | Rank | Model | Provider | Score | Metric | Setting | Reported by | Source | URL | Date | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 1 | o1 | OpenAI | 0.487 | accuracy (total, 0-1) | | Reported by the authors | Paper Table 1 | https://arxiv.org/abs/2501.18062 | 30 Jan 2025 (checked 1 Nov 2026) | | 2 | Claude-3-5-sonnet-20241022 | Anthropic | 0.399 | accuracy (total, 0-1) | | Reported by the authors | Paper Table 1 | https://arxiv.org/abs/2501.18062 | 30 Jan 2025 (checked 1 Nov 2026) | | 3 | GPT-4o | OpenAI | 0.392 | accuracy (total, 0-1) | | Reported by the authors | Paper Table 1 | https://arxiv.org/abs/2501.18062 | 30 Jan 2025 (checked 1 Nov 2026) | | 4 | Numa 1 | Moneda | 0.355 | accuracy (total, 0-1) | Product with tools; 148-question test split; graded by a two-judge panel, not the authors' grader | Run by Moneda | Moneda run, 2026-11-01 | https://benchmarks.finance/method/ | 1 Nov 2026 | | 5 | Llama-3.3-70B-Instruct | Meta | 0.311 | accuracy (total, 0-1) | | Reported by the authors | Paper Table 1 | https://arxiv.org/abs/2501.18062 | 30 Jan 2025 (checked 1 Nov 2026) | ## MortgageTax: accuracy % (higher is better, 5 models) | Rank | Model | Provider | Score | Metric | Setting | Reported by | Source | URL | Date | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 1 | Claude Opus 5 | Anthropic | 72.1 | accuracy % | test set (938 documents), archived board | Official board | Vals.ai MortgageTax leaderboard | https://www.vals.ai/benchmarks/mortgage_tax | 1 Sept 2026 (checked 2 Nov 2026) | | 2 | Claude Fable 5.1 | Anthropic | 70.8 | accuracy % | test set (938 documents), archived board | Official board | Vals.ai MortgageTax leaderboard | https://www.vals.ai/benchmarks/mortgage_tax | 1 Sept 2026 (checked 2 Nov 2026) | | 3 | Claude Opus 4.7 | Anthropic | 70.3 | accuracy % | test set (938 documents), archived board | Official board | Vals.ai MortgageTax leaderboard | https://www.vals.ai/benchmarks/mortgage_tax | 1 Sept 2026 (checked 2 Nov 2026) | | 4 | Claude Sonnet 5 | Anthropic | 70.0 | accuracy % | test set (938 documents), archived board | Official board | Vals.ai MortgageTax leaderboard | https://www.vals.ai/benchmarks/mortgage_tax | 1 Sept 2026 (checked 2 Nov 2026) | | 5 | Claude Opus 4.8 | Anthropic | 69.9 | accuracy % | test set (938 documents), archived board | Official board | Vals.ai MortgageTax leaderboard | https://www.vals.ai/benchmarks/mortgage_tax | 1 Sept 2026 (checked 2 Nov 2026) | ## Moneda FilingsBench: % correct (private split) (higher is better, 1 model) | Rank | Model | Provider | Score | Metric | Setting | Reported by | Source | URL | Date | | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | | 1 | Numa 1 | Moneda | 91.6 | % correct (private split) | 361 private questions, no document given; graded by code against the filings' XBRL data, 13 segment questions by a two-judge panel (not yet human-audited) | Run by Moneda | Moneda run, 2026-11-02 | https://benchmarks.finance/method/ | 2 Nov 2026 | Source: https://benchmarks.finance/best/filings-qa/ Created and maintained by Moneda.