Best Python libraries for PowerPoint files
125 products named in 80 answers across 4 wordings
In nearly every answer
Contested
docx2pptx
How often 10 AI models recommend docx2pptx, what they say about it, and who they recommend instead, on the 1 buying question where it came up.
- Mention rate
- 3%of all answers on this question
- Best standing
- #46of 125 on Best Python libraries for PowerPoint files
- Buying questions
- 1where any model named it
- Never named it
- 8of 10 models
- Since October 25, 2026
- +3 ptsWithin sampling noise on the 8 models that stayed the same
Which models recommend it
Share of each model's answers that named it, at any position · The black tick marks the panel average
Never named it: Claude Haiku 5.5 GPT-6 Luna Gemini 4 Argon Qwen 3.8 Flash DeepSeek V4.1 Flash GLM-5.3 Mistral Large 4 Nemotron 3.5 Super VL. Answers come from each model's training data, so a product released or renamed after a model's knowledge cutoff is unknown to it.
Over time
Share of answers that named it, each time the panel answered · Changes since October 25, 2026 compare only models that stayed the same; gray ones are within sampling noise
| Panel run | Mention rate | Models naming it |
|---|---|---|
| October 26, 2026 | 3% | 2 of 10 |
| October 25, 2026 | 0% | 0 of 10 |
Change since October 25, 2026, by model
- Kimi K30% → 13%+13 pts
- MiniMax M30% → 13%+13 pts
- Claude Haiku 5.50% → 0%±0 pts
- GPT-6 Luna0% → 0%±0 pts
- Gemini 4 Argon0% → 0%±0 pts
- Qwen 3.8 Flash0% → 0%±0 pts
- GLM-5.30% → 0%±0 pts
- Mistral Large 40% → 0%±0 pts
Not compared because the seat changed models: DeepSeek from DeepSeek V4 Pro to DeepSeek V4.1 Flash; NVIDIA from Nemotron 3 Ultra to Nemotron 3.5 Super VL.
What the models say
Each model's one-line reason for recommending it, from its first answer
Best Python libraries for PowerPoint files 1
- Kimi K3
Converts Word documents to PowerPoint, useful for automated document-to-presentation workflows.
Against the competition
Each question's products ranked by the share of all answers that named them, docx2pptx highlighted.
Mention rate by model and question
Share of each model's answers on the question that named it · Hover a cell for the count
| Question | 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 |
|---|---|---|---|---|---|---|---|---|---|---|
| Best Python libraries for PowerPoint files | 13 | 13 |
Does the wording matter?
Share of answers that named it under each way of asking the question · Hover a cell for the exact wording
| Question | List request | Buyer asking for advice | Search query | Worth paying for? |
|---|---|---|---|---|
| Best Python libraries for PowerPoint files | 10 |
Head to head
Against the products named most often on the same questions
With web search
A trial: the same questions answered after each model searched the web · Share of answers that named it, and its place
| Question | Without search | With search | Change |
|---|---|---|---|
| Best Python libraries for PowerPoint files | 3% #47 | not named | −2 pts |
Every other number on this page comes from what the models already know. How searching changes the answers
Work on docx2pptx? Get it tracked every month on the questions your buyers ask, or email sales@modelocracy.com.