Best Python libraries for creating and editing Word files (worth paying for?)

Requested by a visitor · October 26, 2026

We asked 10 models: Which Python libraries for Word documents are worth using? Each named its own top 10.

Asked 4 ways: List request · Buyer asking for advice · Search query · Worth paying for?. Share of voice pools every wording.

Agreement between models: 60%
Same model, run twice: 72%
Different picks: 27

When agreement between models is well below a model's agreement with itself, the split reflects real differences in taste rather than randomness.

The consensus

We asked 10 models: Which Python libraries for Word documents are worth using? Each named its own top 10.

Each cell is the position that model gave the pick; blank means it left the pick off. Click a row for each model's reasoning.

#	Pick	Listed by	Claude Haiku 5.5	GPT-6 Luna	Gemini 4 Argon	Qwen 3.8 Flash	DeepSeek V4.1 Flash	GLM-5.3	Kimi K3	MiniMax M3	Mistral Large 4	Nemotron 3.5 Super VL
1	python-docx	10/10	1	1	1	1	1	1	1	1	1	1
Claude Haiku 5.5 (#1) The de facto standard for reading and writing .docx files in Python. GPT-6 Luna (#1) Best default for creating and editing .docx files; mature, approachable, and widely adopted. Gemini 4 Argon (#1) The definitive open-source standard for creating and modifying Word documents programmatically. Qwen 3.8 Flash (#1) De facto standard for reading and writing Word documents. DeepSeek V4.1 Flash (#1) The default choice for creating and editing .docx files; simple, stable API. GLM-5.3 (#1) De facto standard for creating and editing .docx files; simple, reliable API. Kimi K3 (#1) The standard, best-documented library for creating and editing .docx files. MiniMax M3 (#1) De facto standard for creating and editing .docx files. Mistral Large 4 (#1) The standard choice: creates/modifies .docx files with clean, well-documented API and no dependencies. Nemotron 3.5 Super VL (#1) The standard library for creating and editing .docx files with an intuitive API.
2	docxtpl	9/10	2	2	5	2	2	2	2		5	2
Claude Haiku 5.5 (#2) Jinja2-style templating on top of python-docx, ideal for generating reports. GPT-6 Luna (#2) Excellent for generating .docx documents from templates with Jinja-style variables and loops. Qwen 3.8 Flash (#2) Best Jinja2 templating built directly on python-docx. DeepSeek V4.1 Flash (#2) Jinja2 templating on top of python-docx; best for report generation. GLM-5.3 (#2) Jinja2 templating atop python-docx; ideal for generating documents from templates. Kimi K3 (#2) Simple Jinja2-based templating on top of python-docx, great for reports. Nemotron 3.5 Super VL (#2) Enables Jinja2 templating for .docx documents, ideal for reports and invoices. Mistral Large 4 (#5) Best for Jinja2-templated Word documents with loops, conditionals, and dynamic content.
3	python-docx-template	9/10	6		6	5	3	8	4	7	4	5
DeepSeek V4.1 Flash (#3) Template-heavy workflows for contracts and filled-in forms. Kimi K3 (#4) Deprecated alias concerns aside, widely used templating approach for documents. Mistral Large 4 (#4) Template-centric library, great for generating reports from existing .docx templates. Qwen 3.8 Flash (#5) Established tag-based templating workflow for reports. Nemotron 3.5 Super VL (#5) Supports Jinja2 placeholders and dynamic table generation in .docx templates. Claude Haiku 5.5 (#6) Another templating option, but largely superseded by docxtpl. Gemini 4 Argon (#6) Excels at generating complex documents by combining Jinja2 templating with Word layouts. MiniMax M3 (#7) Excellent Jinja-style templating for Word documents. GLM-5.3 (#8) Popular alternative templating approach merging python-docx with Jinja2-like syntax.
4	Mammoth	8/10	4	5	2		6		6	10	6	7
Gemini 4 Argon (#2) Best-in-class tool for cleanly converting Word documents into semantic HTML or Markdown. Claude Haiku 5.5 (#4) Converts Word documents to clean HTML or Markdown, focused on semantic output. GPT-6 Luna (#5) Converts .docx to clean HTML, especially useful when semantic content matters more than exact styling. DeepSeek V4.1 Flash (#6) Clean DOCX-to-HTML/Markdown conversion with sensible semantic mapping. Kimi K3 (#6) Best for clean .docx-to-HTML conversion without messy inline styling. Nemotron 3.5 Super VL (#7) Extracts clean HTML from .docx files for web publishing and migration. MiniMax M3 (#10) Converts Word docs to clean HTML with strong style handling.
5	docx2txt	6/10		7	7			4		2	2	3
MiniMax M3 (#2) Best lightweight extractor for plain text from Word documents. Mistral Large 4 (#2) Fast, simple text extraction from .docx files without Microsoft Word dependencies. Nemotron 3.5 Super VL (#3) Lightweight text extraction from Word documents without heavy dependencies. GLM-5.3 (#4) Lightweight, dependable plain-text extraction from .docx files. GPT-6 Luna (#7) Lightweight choice for quickly extracting plain text from .docx files. Gemini 4 Argon (#7) Lightweight, fast utility specifically designed for scraping plain text and images from files.
6	docx2pdf	8/10	3		10	4	7	9	10	3		6
Claude Haiku 5.5 (#3) Simple conversion of Word documents to PDF, though it needs Word or macOS. Qwen 3.8 Flash (#4) Simplest reliable Word-to-PDF conversion on Windows/macOS. GLM-5.3 (#9) Easy .docx to PDF conversion, leveraging Word or LibreOffice under the hood.
7	Spire.Doc	6/10		8		3	4	10	5	8
Qwen 3.8 Flash (#3) Rich format conversion without needing Microsoft Office installed. DeepSeek V4.1 Flash (#4) Strong commercial alternative with good conversion and mail-merge support. Kimi K3 (#5) Solid commercial alternative with broad format conversion and free tier. GPT-6 Luna (#8) Commercial toolkit with broad Word editing and conversion capabilities. MiniMax M3 (#8) Free-tier commercial alternative for read/write/convert. GLM-5.3 (#10) Feature-rich commercial alternative handling conversion, mail merge, and complex layouts.
8	Aspose.Words for Python	6/10		6	9	8	9	3		4
GLM-5.3 (#3) Commercial library with unmatched format fidelity, conversions, and advanced features. MiniMax M3 (#4) Powerful commercial library with full document fidelity. GPT-6 Luna (#6) Powerful commercial option for conversion, rendering, and complex document manipulation. Gemini 4 Argon (#9) Enterprise-grade commercial library offering unmatched layout fidelity and advanced manipulation without Office installed.
9	docxcompose	6/10	9	4		9		5	7	5
GPT-6 Luna (#4) Reliable merging and appending of Word documents while preserving much of their structure. MiniMax M3 (#5) Useful for merging and composing multiple Word files. Kimi K3 (#7) Specializes in merging and concatenating multiple .docx files cleanly. Qwen 3.8 Flash (#9) Cleanly merges multiple Word documents preserving styles.
10	Aspose.Words	5/10	7			7	5		3		9
Kimi K3 (#3) Most powerful commercial option with rendering, conversion, and mail merge. DeepSeek V4.1 Flash (#5) Commercial powerhouse for DOCX, DOC, PDF, and complex layout fidelity. Claude Haiku 5.5 (#7) Commercial, feature-complete Word engine with a Python API for complex layouts. Qwen 3.8 Flash (#7) Enterprise-grade parsing, merging, and rendering capabilities.
11	Docx2python	4/10		3	4		10		8
GPT-6 Luna (#3) Practical extraction of paragraphs, tables, headers, footers, and document structure. Gemini 4 Argon (#4) Superior data extraction tool that pulls text, tables, headers, and images effortlessly. DeepSeek V4.1 Flash (#10) Reliable extraction of text, tables, and structure from .docx files.
12	pypandoc	5/10	10		3		8	7	9
Gemini 4 Argon (#3) Unmatched versatility for converting between Word and dozens of other document formats. Kimi K3 (#9) Converts .docx to and from many formats via Pandoc, excellent interoperability.
13	PyDocX	1/10									3
Mistral Large 4 (#3) Alternative name sometimes used; essentially python-docx functionality with template support.
14	docx-mailmerge	3/10	8	9								8
Claude Haiku 5.5 (#8) Straightforward mail merge for filling Word templates with field data. Nemotron 3.5 Super VL (#8) Simple mail-merge functionality for filling Word templates with data.
15	docx	1/10										4
Nemotron 3.5 Super VL (#4) A practical wrapper around python-docx used widely for Word document automation.

12 lower-scoring picks are not shown; every ballot below lists them in full.

Most divisive

Picks most models listed, at very different positions

Mammoth#2 for Gemini 4 Argon #10 for MiniMax M3
docx2pdf#3 for Claude Haiku 5.5 #10 for Kimi K3
Spire.Doc#3 for Qwen 3.8 Flash #10 for GLM-5.3

Hot takes

Picks that appear on only one ballot

PyDocX at #3, only Mistral Large 4
docx at #4, only Nemotron 3.5 Super VL
Pandoc at #5, only Claude Haiku 5.5
Docx4Python at #6, only Qwen 3.8 Flash
mailmerge at #6, only GLM-5.3
openpyxl at #6, only MiniMax M3
Mako + docx at #7, only Mistral Large 4
Win32com at #8, only Mistral Large 4
pandas at #9, only MiniMax M3
docx-image at #9, only Nemotron 3.5 Super VL
msoffcrypto-tool at #10, only Qwen 3.8 Flash
LibreOffice UNO (Python) at #10, only Mistral Large 4

Every ballot

Hover a pick to find it on the other ballots. Marked picks appear on no other ballot.

Claude Haiku 5.5

python-docx
docxtpl
docx2pdf
Mammoth
Pandoc
python-docx-template
Aspose.Words
docx-mailmerge
docxcompose
pypandoc

78% with consensus · 85% self-consistent · knowledge cutoff June 2026

GPT-6 Luna

python-docx
docxtpl
Docx2python
docxcompose
Mammoth
Aspose.Words for Python
docx2txt
Spire.Doc
docx-mailmerge
pywin32

73% with consensus · 91% self-consistent · knowledge cutoff May 18, 2026

Gemini 4 Argon

python-docx
Mammoth
pypandoc
Docx2python
docxtpl
python-docx-template
docx2txt
pywin32
Aspose.Words for Python
docx2pdf

63% with consensus · 72% self-consistent · knowledge cutoff March 2026

Qwen 3.8 Flash

python-docx
docxtpl
Spire.Doc
docx2pdf
python-docx-template
Docx4Python
Aspose.Words
Aspose.Words for Python
docxcompose
msoffcrypto-tool

76% with consensus · 76% self-consistent · knowledge cutoff not published

DeepSeek V4.1 Flash

python-docx
docxtpl
python-docx-template
Spire.Doc
Aspose.Words
Mammoth
docx2pdf
pypandoc
Aspose.Words for Python
Docx2python

85% with consensus · 55% self-consistent · knowledge cutoff not published

GLM-5.3

python-docx
docxtpl
Aspose.Words for Python
docx2txt
docxcompose
mailmerge
pypandoc
python-docx-template
docx2pdf
Spire.Doc

72% with consensus · 59% self-consistent · knowledge cutoff not published

Kimi K3

python-docx
docxtpl
Aspose.Words
python-docx-template
Spire.Doc
Mammoth
docxcompose
Docx2python
pypandoc
docx2pdf

78% with consensus · 77% self-consistent · knowledge cutoff not published

MiniMax M3

python-docx
docx2txt
docx2pdf
Aspose.Words for Python
docxcompose
openpyxl
python-docx-template
Spire.Doc
pandas
Mammoth

58% with consensus · 54% self-consistent · knowledge cutoff not published

Mistral Large 4

python-docx
docx2txt
PyDocX
python-docx-template
docxtpl
Mammoth
Mako + docx
Win32com
Aspose.Words
LibreOffice UNO (Python)

65% with consensus · 78% self-consistent · knowledge cutoff not published

Nemotron 3.5 Super VL

python-docx
docxtpl
docx2txt
docx
python-docx-template
docx2pdf
Mammoth
docx-mailmerge
docx-image
docx-table

79% with consensus · 71% self-consistent · knowledge cutoff not published

Who agrees with whom

Overlap between two models' lists, weighted toward the top · 100 means identical · Color runs from 46 (lightest) to 88 (darkest)

	Claude Haiku 5.5	GPT-6 Luna	Gemini 4 Argon	Qwen 3.8 Flash	DeepSeek V4.1 Flash	GLM-5.3	Kimi K3	MiniMax M3	Mistral Large 4	Nemotron 3.5 Super VL
Claude Haiku 5.5		67	59	76	74	62	73	55	54	72
GPT-6 Luna	67		65	63	66	73	70	54	51	65
Gemini 4 Argon	59	65		50	58	54	57	46	56	55
Qwen 3.8 Flash	76	63	50		82	65	76	55	51	69
DeepSeek V4.1 Flash	74	66	58	82		65	88	47	59	71
GLM-5.3	62	73	54	65	65		65	67	55	70
Kimi K3	73	70	57	76	88	65		46	59	68
MiniMax M3	55	54	46	55	47	67	46		61	59
Mistral Large 4	54	51	56	51	59	55	59	61		67
Nemotron 3.5 Super VL	72	65	55	69	71	70	68	59	67