Finance AI Index

Index › Vendors › Python · September 2026 Edition

1 category · Named, not ranked

Python

2Judge labels

0First choices

0Negative labels

2 of 12Models named it

1Category

September 2026 Edition. Every number here is derived from the raw labels under vendor table vv2026-09.2, every buyer segment counted.

Standing

2 labels, too few to rank

A product needs 10 labels in a category before a share or quadrant is stated. Python was named 2 times in Financial modeling, where Datarails led with 19%. The labels and the evidence are below, counted exactly.

By buyer segmentRead the same way at every buyer size.

Small businessnot named

No model named it for this buyer.

Mid-market32 of 114

under the label threshold

Enterprisenot named

No model named it for this buyer.

In financial modeling · each standing computed within its segment · bars are 0 to 100 · the accent bar is the product's own best reading

Standing by category

Every category where a model named Python for a mid-market B2B company. Share is first choices across the direct, paraphrase, budget and scale prompts; rank is within every product named in that category.

Category	Function	Share	Rank	Negative rate	Labels	Quadrant
Financial modeling and scenario planning	Planning and analysis	0%	32 of 114	0%	2	under 10 labels · led by Datarails at 19%

Movement

This is the first edition on this tier, so no move can be computed for Python yet. From the next edition this section shows, per buyer segment, whether its share moved by more than the measured noise floor.

By model

How each model treated Python across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.

Model	Alternative	Labels
Claude Haiku 4.5	0	0
GPT-5.4 mini	1	1
Gemini 3.5 Flash	0	0
Perplexity Sonar	0	0
Grok 4.1 Fast	0	0
Mistral Small	0	0
DeepSeek V4 Flash	0	0
Llama 4 Maverick	0	0
Qwen 3.7 Flash	0	0
Kimi K2	0	0
GLM 4.7 FlashX	1	1
MiniMax M2.5	0	0

By framing

Which of the six questions produced the naming. By model says how often; this says asked what. The first-choice count on the right carries the marks of the models that produced it.

FramingLabels by classFirst choices

Direct0 labelsNone

Paraphrase0 labelsNone

Comparative2 labelsNone

Budget-constrained0 labelsNone

Scale-constrained0 labelsNone

Negative0 labelsNone

First choiceAlternativeMentionNegative2 labels in all, every segment counted; 0 of the 0 first choices count toward share, since the comparative and negative framings do not. The bar is one segment per label class, to scale within the framing.

What the models said for it

Verbatim evidence the judge attached to positive labels.

“Advanced, programmatic modeling | Large datasets, complex calculations, Monte Carlo, optimization” GLM 4.7 FlashX · Financial modeling · comparative prompt · alternative

“Need flexible ML or automation? Python” GPT-5.4 mini · Financial modeling · comparative prompt · alternative

And against it

Verbatim evidence attached to negative labels. A warning on a product with few labels is a warning; on a product with many, it is one voice among them.

No model argued against it.

Named alongside

The products named in the same answers as Python, over the 2 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Python was named but was not.

ProductSame answerTook the first choice insteadHead to head

Excel/Google Sheets1 of 21Not in the top three

Microsoft Excel1 of 21Not in the top three

Alteryx1 of 20Not in the top three

Anaplan1 of 20Not in the top three

Google Sheets1 of 20Not in the top three

Jupyter1 of 20Not in the top three

Jupyter Notebook / JupyterLab1 of 20Not in the top three

KNIME1 of 20Not in the top three

MATLAB1 of 20Not in the top three

Macabacus1 of 20Not in the top three

A head-to-head page exists where both products are in a category's top three. The other rows are the same fact without a page behind them, so they link to the product instead.

What carried it into the answer

The sites and pages cited by the answers that named Python. A fact about retrieval, not a lever on the model.

Citations exist only for the models that return a source list, four of the twelve in this edition, so these counts come from 1 of the 2 answers that named Python and are not a share of its labels.

Domains cited

arxiv.org1

cardanit.com1

datacamp.com1

datamation.com1

deepscienceresearch.com1

en.wikipedia.org1

ethical.institute1

finamodel.com1

financealliance.io1

g2.com1

Ten of the ten domain citations in answers naming Python came from somebody else's page.

Pages cited

arxiv.org/html/2508.04035v11

cardanit.com/blog/best-business-process-modeling-tools1

datacamp.com/blog/data-modeling-tools1

datamation.com/applications/top-data-modeling-tools1

deepscienceresearch.com/dsr/catalog/book/6/chapter/611

en.wikipedia.org/wiki/Comparison_of_data_modeling_tools1

ethical.institute/open-source/production-ml-list1

finamodel.com/blog/top-tools-for-financial-modelling1

Pages are listed as the models cited them.

Names read as Python

What the judge wrote, as written, with how often. The vendor table decides that these count as Python; a claim can dispute any of them.

Python (pandas, NumPy, SciPy) 1

Is this your product?

Claim this page

Claiming is free and changes nothing in the data. A claimed page shows a verified contact who is told when each edition publishes and when Python's standing changes by more than the noise floor; the right to propose corrections to the vendor table, meaning names the judge wrote that should or should not read as Python, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.

It does not get any change to labels, shares or verdicts, any preview, or any say over which quotes appear. A verification link goes to your work email; an address at python.com is approved on the spot, any other address is reviewed by hand.

Your name and company appear on the claimed page, or the company alone if you ask below. A title and a LinkedIn address appear there too if you give them, and are left off if you do not. Your email address is never published.