AI models for finance and financial analysis
Fintech and FP&A teams use LLMs for memos, variance narratives, and research. Semrush ~260/mo for “best ai for finance”. This list prioritizes rigor and professional tone — not investment advice.
Models in this collection
| Model | Type | Context | Price |
|---|---|---|---|
| Chat | 1M tokens | $3.2702/M in · $16.3509/M out | |
| Chat | 272k tokens | $5.4503/M in · $32.7018/M out | |
| Chat | 2M tokens | $1.3626/M in · $10.9006/M out | |
| Chat | 1M tokens | $5.4503/M in · $27.2515/M out | |
| Chat | 200k tokens | $1.1991/M in · $4.7963/M out | |
| Chat | 1M tokens | $0.4742/M in · $0.9484/M out | |
| Chat | 272k tokens | $0.8175/M in · $4.9053/M out | |
| Chat | 200k tokens | $1.0901/M in · $5.4503/M out |
Why these models
Sonnet/GPT/Gemini Pro for memos; Opus/o3-mini when reasoning is dense; Haiku/mini to classify tickets and statements.
Use them with Geek Hub
One OpenAI-compatible base URL and API key. Swap any model id from this list without rewriting your client.
Get an API keyFAQ
- Is this financial advice?
- No. It is drafting/analysis assistance. Follow your internal compliance and disclaimers.
- Sensitive data?
- Check ZDR/caps and provider policies. Use separate keys per environment.
- Exact numbers?
- Pass tables as data; do not let the model “remember” prices. Verify math outside the LLM.