Financial knowledge
Accounting, markets, economics, valuation, and professional-exam concepts represented in the category.
Best AI Models for Finance in 2026
Qwen3.7 Max currently leads the LLM Stats finance category, followed by Qwen3.5-397B-A17B. This rank covers model evidence; evaluate professional software and advice separately.
LLM Stats ResearchSeptember 2026227 models32 benchmarks
Reviewed by Jonathan Chavez · 227 models across 32 live benchmarksSources & review
Review boundary
Data methodology reviewed internally; not reviewed by a CPA, CFA charterholder, or investment adviser.
Scope and disclosure
This page ranks underlying model evidence. Professional software products require a separate workflow and controls review. LLM Stats accepts no payment for ranking position. Read the methodology or report a correction.
Evaluating the complete product?
Compare sources, workflow, integrations, security, and price in the professional buyer guide.
At a glance
| Model | Best for | Top strength | Watch out | Cost · Context |
|---|---|---|---|---|
| Qwen3.7 Max Alibaba Cloud / Qwen Team | Alibaba's newest — strongest open-weight Asian frontier | Excellent multilingual coverage (50+ languages) | Western provider coverage lags | $1.25 / $3.75 1.0M ctx |
| Qwen3.5-397B-A17B Alibaba Cloud / Qwen Team | Earlier Qwen 3 — still capable, especially MoE variants | MoE architecture gives strong quality at low active-parameter cost | Newer versions lead it | $0.45 / $3.00 262K ctx |
| Qwen3.6 Plus Alibaba Cloud / Qwen Team | Mature Qwen generation — strong all-rounder | Open weights, broad language support | 3.7 line now ahead on the hardest tasks | $0.50 / $3.00 1.0M ctx |
| Qwen3.7-Plus Alibaba Cloud / Qwen Team | Alibaba's newest — strongest open-weight Asian frontier | Excellent multilingual coverage (50+ languages) | Western provider coverage lags | — |
| Qwen3.5-122B-A10B Alibaba Cloud / Qwen Team | Earlier Qwen 3 — still capable, especially MoE variants | MoE architecture gives strong quality at low active-parameter cost | Newer versions lead it | $0.29 / $2.40 262K ctx |
- Qwen3.7 Max$1.25 / $3.75
Alibaba's newest — strongest open-weight Asian frontier
- Strength
- Excellent multilingual coverage (50+ languages)
- Watch out
- Western provider coverage lags
- Qwen3.5-397B-A17B$0.45 / $3.00
Earlier Qwen 3 — still capable, especially MoE variants
- Strength
- MoE architecture gives strong quality at low active-parameter cost
- Watch out
- Newer versions lead it
- Qwen3.6 Plus$0.50 / $3.00
Mature Qwen generation — strong all-rounder
- Strength
- Open weights, broad language support
- Watch out
- 3.7 line now ahead on the hardest tasks
Alibaba's newest — strongest open-weight Asian frontier
- Strength
- Excellent multilingual coverage (50+ languages)
- Watch out
- Western provider coverage lags
- Qwen3.5-122B-A10B$0.29 / $2.40
Earlier Qwen 3 — still capable, especially MoE variants
- Strength
- MoE architecture gives strong quality at low active-parameter cost
- Watch out
- Newer versions lead it
What the finance benchmarks measure
Benchmarks are controlled evidence. They help narrow a model shortlist, but they do not reproduce a complete professional workflow.
Quantitative reasoning
Multi-step calculations, numerical interpretation, assumptions, and finance-specific problem solving.
Document understanding
Extracting and reasoning across statements, filings, tables, disclosures, and narrative context.
Evidence breadth
Coverage across different evaluations, with sparse evidence treated as uncertainty rather than a perfect score.
Choose a model for your work
Financial modeling
Prioritize quantitative reasoning, tool use, and reliable structured output.
Recalculate key outputs and audit formulas, units, dates, and signs.
Investment research
Combine finance strength with search, long context, and source-grounded retrieval.
A trained model does not include every live filing, transcript, estimate, or price.
FP&A
Consistency, spreadsheet integration, narrative quality, speed, and cost all matter.
Reconcile every material figure to the ERP, warehouse, or approved planning model.
Accounting and controls
Favor careful extraction, classification, policy reasoning, and explicit assumptions.
Qualified reviewers remain responsible for treatment, evidence, and sign-off.
Methodology
Full LLM Stats methodologyThe finance category combines the available finance, accounting, economics, and analytical evaluations rather than presenting one exam as a complete measure of professional ability. The live table shows benchmark coverage and individual results.
Where category-index evidence is available, LLM Stats uses an uncertainty-aware conservative score. Otherwise the summary uses benchmark coverage and normalized performance. A category score is a comparison signal—not a forecast-accuracy rate or investment recommendation.
Model capability is only one layer of a finance system. Production value also depends on spreadsheet execution, source-data permissions, market-data entitlements, formula traceability, audit logs, review gates, and integration with the system of record.
High-consequence use: The leaderboard is comparative research, not legal, accounting, tax, or investment advice. Validate the selected model inside the exact product, data, jurisdiction, and review process you plan to use.
01
Freeze
Record model version, date, benchmark set, and category.
02
Inspect
Open the visible benchmark table and note missing results.
03
Recompute
Compare normalized results and evidence coverage.
04
Validate
Run a separate known-answer test in the deployed product.
Frequently asked questions
Which AI model is best for finance?
The live table above identifies the current category leader from available finance evidence. The best deployment still depends on the task: workbook execution, research, FP&A, accounting, risk, and client communication require different data, tools, and controls.
What do finance AI benchmarks measure?
They can measure financial and accounting knowledge, quantitative reasoning, economics, statement interpretation, and exam-style questions. They do not fully measure live-data accuracy, spreadsheet execution, forecasting judgment, auditability, or the quality of an enterprise deployment.
Can the highest-ranked finance model make investment decisions?
A high rank does not make a model a fiduciary or establish suitability for autonomous decisions. Use model output as reviewed decision support, with current licensed data and accountable professionals responsible for conclusions and actions.
How should finance teams test an AI model?
Use representative workbooks, filings, policies, and known-answer tasks. Measure numerical accuracy, formula integrity, source traceability, correction time, repeatability, latency, cost, and performance when information is missing or contradictory.