Comparison
ChatGPT vs Smalt AI
for finance work.
ChatGPT is a strong general-purpose AI assistant. Smalt AI is purpose-built for finance work — DCFs, LBOs, decks, sourced research. Both have a place. Here's an honest read on which one fits which job, with the caveats neither marketing page tells you.
The short answer
Use ChatGPT for general writing, brainstorming, code, and quick research where citations and verifiability aren't critical. Use Smalt AI when the output needs to be a real deliverable — an Excel model with live formulas, a deck with editable text, research with sourced citations, or work that touches financial regulators or an investment committee.
Capability comparison
| Capability | ChatGPT | Smalt AI |
|---|---|---|
| General Q&A, brainstorming, writing | Excellent | Good (not the focus) |
| Code generation | Strong (general) | Sufficient (focus is finance) |
| DCF / LBO / 3-statement Excel models | Returns text/markdown tables. Cells contain values, not formulas. Not an actual workbook. | Returns a working .xlsx with =SUM, =NPV, =XIRR. Change a driver, the model recalculates. |
| PowerPoint generation | Markdown outline. No native .pptx output. | Native editable .pptx with consulting-grade typography, charts, analyst right-rail commentary. |
| Web research with citations | Browse mode (when enabled). Citations sometimes hallucinated. | Paragraph-level citations to filings, news, expert calls. Source links verified. |
| Filings analysis (10-K, 10-Q) | Up to 200K-token context (GPT-4o). Can chunk longer docs. | 1M-token Claude context for entire 10-Ks, four quarters of transcripts in one pass. |
| Excel file editing (BYO workbook) | Code interpreter can manipulate uploaded Excel files but returns hardcoded outputs | Native xlsx round-trip — preserves formulas, adds sheets, returns a working file |
| Multi-agent / agent orchestration | Custom GPTs, beta agent features | Single chat — sub-agent routing happens behind the scenes; you don't manage it |
| Pricing | $20/mo Plus, $200/mo Pro, $25/seat Enterprise | Free tier (500 credits, no card), Basic ~$18/mo, Pro ~$45/mo, Enterprise self-host |
| Data residency / self-hosting | Enterprise plans only; managed in OpenAI infrastructure | Enterprise self-hosting available — full data residency on your infrastructure |
Where Smalt AI is materially different
The defining gap is output fidelity. Ask ChatGPT to "build a DCF for Apple" and you get a markdown table where the numbers are LLM-typed — not formulas. Change a driver and nothing recalculates because there's nothing to recalculate. The output is a description of a model, not a model.
Smalt AI returns a real .xlsx file. Cells contain =NPV(WACC, FCF_range), =SUM(...), =INDEX/MATCH. The model has 14 linked sheets — assumptions, revenue schedule, COGS, OpEx, working capital, capex, debt, tax, three statements, WACC, DCF valuation, three 5×5 sensitivity tables. Change a driver, the whole model recalculates because it's an actual model.
The same gap exists in PowerPoint. ChatGPT outlines decks in markdown. Smalt AI generates native .pptx with consulting-grade typography, real charts, and an analyst's right-rail commentary on every slide — the Bain pattern. Editable. Watermark-free.
Where ChatGPT is the right tool
For general-purpose work — drafting an email, writing code, brainstorming, summarising an article, casual research — ChatGPT is excellent and extremely well-rounded. Its general intelligence, reasoning ability, and code generation are state-of-the-art. The Plus tier at $20/mo is hard to beat for individual productivity.
For technical or non-finance work — software engineering, science writing, language learning, creative writing — ChatGPT is the better tool. Smalt AI is optimised for finance and analyst workflows; we don't claim parity outside that domain.
Where Smalt AI is the right tool
For real finance deliverables — anything that needs to be opened in Excel or PowerPoint and presented to an investment committee, a board, or a regulator. The output has to be a working artefact, not a description of one.
For sourced research — when you need every claim to trace back to a filing, a transcript, or a reputable source. Smalt AI's research outputs include paragraph-level citations to verifiable sources; ChatGPT's browse mode is improving but inconsistent.
For long-context document analysis — full 10-Ks, multi-year transcripts, hundreds of pages of expert call notes. Claude's 1M-token context (used by Smalt AI) handles it in one pass. ChatGPT chunks.
For data residency and compliance — Enterprise self-hosting on your infrastructure. ChatGPT keeps everything in OpenAI's environment.
Honest caveats
- Smalt AI is narrower than ChatGPT by design. If you want one assistant for everything, ChatGPT covers more ground.
- Smalt AI is newer. ChatGPT has years of refinement and an enormous ecosystem of integrations and custom GPTs.
- Both tools can hallucinate. Smalt AI mitigates with sourced citations and quality checks (e.g., the balance-sheet must balance, the WACC must be in range), but no AI is perfectly reliable on novel reasoning.
- Pricing is at credit-metered cost at Smalt AI; subscription seat-priced at OpenAI. Different math depending on usage pattern.
The summary
ChatGPT is the best general-purpose AI assistant available. Smalt AI is the best AI virtual employee for finance work — purpose-built for the deliverables that matter to analysts, investors, and finance teams. They aren't competitors so much as complements: most finance professionals will use ChatGPT for general productivity and Smalt AI when the output has to be a real model, deck, or sourced research artefact.
500 free credits, no credit card. Try Smalt AI on a real workflow and decide.
See the difference on a real workflow.
Build a DCF, generate a deck, run a research scan — see the output yourself.