Cost of Analyzing Financial Reports with LLMs
Filings and transcripts run to tens of thousands of tokens each. Extraction output is small and structured. Outputs are analytical aids, not investment advice.
Typical monthly workload
- Input tokens
- 40,000,000
- Output tokens
- 1,500,000
- Requests / day
- 400
Illustrative estimate. Adjust the sliders below to match your own volume.
Recommended setup
Extract fields with a cheap long-context model and verify numeric values programmatically against source tables.
Monthly cost by model for this workload
| Model | Input / 1M | Output / 1M | Est. monthly cost |
|---|---|---|---|
| Gemini 1.5 Flash | $0.075 | $0.30 | $3.45 |
| DeepSeek V3 / V2.5 | $0.140 | $0.28 | $6.02 |
| GPT-4o Mini | $0.150 | $0.60 | $6.90 |
| Llama 3.3 70B (Groq/Together) | $0.590 | $0.79 | $24.78 |
| Claude 3.5 Haiku | $0.800 | $4.00 | $38.00 |
| o1-mini | $1.100 | $4.40 | $50.60 |
| Gemini 1.5 Pro | $1.250 | $5.00 | $57.50 |
| Mistral Large 2 | $2.000 | $6.00 | $89.00 |
| GPT-4o (Omni) | $2.500 | $10.00 | $115.00 |
| Claude 3.5 Sonnet | $3.000 | $15.00 | $142.50 |
| o1 (Reasoning) | $15.000 | $60.00 | $690.00 |
Computed from list prices and the workload above (40,000,000 input and 1,500,000 output tokens per month), with no caching or batch discounts. Real bills vary.
How to cut this cost
- Verify numbers in code
Never trust model arithmetic. Recompute totals and ratios from extracted values.
- Process each filing once
Store extracted JSON per filing so repeat questions hit your database, not the API.
Simulate your own spend
Quick Workload Presets
Pick a ready-made scenario or customize your token volume below.
Token & Usage Parameters
By switching or routing background tasks from GPT-4o to Gemini 1.5 Flash, your team saves up to $2,270 annually.
Lowest cost per token, high-frequency tasks, real-time audio/video
State-of-the-art open economics, high-performance general intelligence
High-volume text processing, fast chatbots, classification
Open-weights privacy, self-hosting or ultra-cheap hosted inferencing
Rapid code completion, customer service, structured data extraction
Fast STEM reasoning, competitive programming at lower cost
Massive context (2M tokens), full video/audio analysis, large codebases
Multilingual tasks, European compliance, enterprise code generation
Complex multimodal reasoning, coding, and production apps
Software engineering, nuanced writing, complex agentic workflows
Advanced mathematics, algorithmic coding, PhD-level scientific logic
Frequently asked questions
Should I rely on LLM output for investment decisions?
No. Models can misread tables or hallucinate figures. Use them to speed up reading and always check against the primary source.