Small business▲+2Since September 2026: 2% → 4%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
4%from 2% in September 2026
Inside the floor by 9 pointsRank 15 → 9 of 131
1 category · RankedTensorFlow
26Judge labels
3First choices
4Negative labels
11 / 14Models named it
1Category
October 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-10.8, every buyer segment counted.
Best standing
3% in ML platforms for small business buyers
Rank 11 of 107 in the mid-market standingaccepted challenger
0 of 14 models made it the first choice on the direct prompt; 0% of its 10 labels there were negative.
What the models named instead of TensorFlow →By buyer segmentRead the same way at every buyer size.
Small business9 of 139
3%14 labels
accepted challenger
Mid-market11 of 107
2%10 labels
accepted challenger
Enterprise64 of 65
0%2 labels
under the label threshold
In ml platforms · 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 TensorFlow 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 | Since September 2026 |
|---|---|---|---|---|---|---|---|
| ML platforms | Data platform | 2% | 11 of 107 | 0% | 10 | accepted challenger | ▼−2Since September 2026: 4% → 2%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
Movement
Since September 2026, TensorFlow held within the floor in its one category: no change cleared 11 points.
Best category · ML platforms · by segment
Mid-market▼−2Since September 2026: 4% → 2%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
2%from 4% in September 2026
Inside the floor by 9 pointsRank 7 → 11 of 97
EnterprisenewNew since September 2026: not ranked then, 0% now.
0%from 0% in September 2026
Inside the floor by 11 pointsRank 54 of 55, unchanged
All categories · Mid-market
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| ML platforms | 4% | 2% | ▼−2Since September 2026: 4% → 2%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 7 → 11 of 107 |
Shares here are read over the models both editions asked, so they can differ by a point or two from the standing above, which counts every model in this edition.
The floor is 11 points of share, measured: how far the models move a leader on their own when the same questions are asked twice with nothing changed. A larger change is movement; a smaller one is noise, and both are shown. Movement is read over the twelve models both editions asked; GPT-6 Luna, Muse Glimmer 30B joined this edition and are in the standing but not yet in the comparison. How the floor is measured · The editions
By model
How each model treated TensorFlow across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.ShowHide
By model
How each model treated TensorFlow across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.
ShowHide| Model | First choice | Alternative | Mention | Negative | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 0 | 0 | 1 | 0 | 1 |
| GPT-5.4 mini | 0 | 0 | 0 | 0 | 0 |
| Gemini 3.5 Flash | 0 | 0 | 0 | 0 | 0 |
| Perplexity Sonar | 0 | 1 | 0 | 0 | 1 |
| Grok 4.20 | 0 | 0 | 0 | 0 | 0 |
| Mistral Small | 0 | 0 | 1 | 0 | 1 |
| DeepSeek V4 Flash | 0 | 1 | 0 | 0 | 1 |
| Llama 4 Maverick | 0 | 0 | 0 | 0 | 0 |
| Qwen 3.7 Flash | 0 | 1 | 1 | 0 | 2 |
| Kimi K2 | 1 | 1 | 0 | 0 | 2 |
| GLM 4.7 FlashX | 0 | 0 | 0 | 0 | 0 |
| MiniMax M2.5 | 0 | 1 | 0 | 0 | 1 |
| GPT-6 Luna | 0 | 0 | 0 | 0 | 0 |
| Muse Glimmer 30B | 0 | 0 | 1 | 0 | 1 |
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
Direct4 labelsNone
Paraphrase0 labelsNone
Comparative4 labelsNone
Budget-constrained12 labels3
Scale-constrained1 labelNone
Negative5 labelsNone
First choiceAlternativeMentionNegative26 labels in all, every segment counted; 3 of the 3 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.
“start with open-source tools like TensorFlow or PyTorch combined with Google Colab” Kimi K2 · ML platforms · budget prompt · first choice
“For flexibility: Consider open-source options (TensorFlow, PyTorch) with proper security management” MiniMax M2.5 · ML platforms · negative prompt · alternative
“especially scikit-learn, XGBoost, and TensorFlow—because the software itself is free” Perplexity Sonar · ML platforms · budget prompt · alternative
“Open-source frameworks (scikit-learn, PyTorch, TensorFlow, Hugging Face)” Kimi K2 · ML platforms · negative 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 TensorFlow, over the 26 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and TensorFlow was named but was not.ShowHide
Named alongside
The products named in the same answers as TensorFlow, over the 26 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and TensorFlow was named but was not.
ShowHideProductSame answerTook the first choice insteadHead to head
A head-to-head page exists where both products are among a category's top eight. 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 TensorFlow. A fact about retrieval, not a lever on the model.
Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 23 of the 26 answers that named TensorFlow and are not a share of its labels.
Domains cited
g2.com18
deepusecase.com12
spotsaas.com12
byteplus.com10
it-ai-index.com10
eweek.com9
checkthat.ai8
us.fitgap.com7
learn.g2.com6
dataiku.com5
Ninety-seven of the ninety-seven domain citations in answers naming TensorFlow came from somebody else's page.
Pages cited
Pages are listed as the models cited them.
Search and answers
tensorflow.org is not in Google's top ten for any of the category's searches. In the answers, TensorFlow takes 2% of first choices and Azure Machine Learning takes 21%.ShowHide
Search and answers
tensorflow.org is not in Google's top ten for any of the category's searches. In the answers, TensorFlow takes 2% of first choices and Azure Machine Learning takes 21%.
ShowHideIn search
Google, US estimatesPosition for “machine learning platform”
–
not in the top ten
Position for “machine learning platforms”
–
not in the top ten
- Searches for its name, Google
- 18,100 a month (“tensorflow”)
- AI search demand for its name, est.
- 2,745 a month
- Organic visits to its site
- about 198,535 a month
- Searches its site ranks for
- 12,439 · 1,245 in the top three
- Sites linking to it
- 38,501
- Paid Google search
- No ads found in the estimate; that does not mean it runs none
In answers
This editionShare of first choices
2%
rank 11 of 107 in ML platforms
Segment leader
21%
Azure Machine Learning
- First choices
- 3 across its categories
- Named in
- 26 answers
- Its own site cited
- in 23 of the answers that named it
Search figures are US estimates from DataForSEO, read September 28, 2026; AI search demand is its modeled, directional estimate, not a count of queries to any assistant. The answers are this edition's. Two measurements side by side: neither is read as the cause of the other.
What it publishes
ShowHide
What it publishes
ShowHideAddresses on tensorflow.org
13,181
subdomains included
Content
627
counted in the table below
Documentation
3
Product · Integration
18 · 0
| Kind | Pages | Last 90 days | 2025-10 to 2026-09 | Latest | Categories named |
|---|---|---|---|---|---|
| Blog | 406 | 0 | 2025-08-19 | ||
| Report or ebook | 178 | 0 | 2022-05-01 | ||
| Template or tool | 21 | undated | |||
| Conference or event | 16 | 0 | 2023-05-26 | ||
| Comparison | 2 | undated | |||
| Podcast or video | 2 | undated | |||
| Case study | 1 | 0 | 2023-08-09 | ||
| News or press | 1 | undated |
Most recent
- 2025-08-19Whats new in tensorflow 2 20 blog
- 2025-03-13Whats new in tensorflow 2 19 blog
- 2024-12-05Introducing wake vision new dataset for person detection in tinyml blog
- 2024-11-19Mlsysbookai principles and practices of machine learning systems engineering blog
- 2024-10-28Whats new in tensorflow 218 blog
- 2024-07-18Whats new in tensorflow 217 blog
How it is countedHide how it is counted
Every page tensorflow.org exposes, subdomains included. Kind is read from the address and title. The last 90 days, the latest date and the twelve months count pages by when they were published, from the site's feeds, a date in the address, or the page's own publication date, read from up to a hundred of its most recently changed pages; a page that says only when it last changed is counted in its kind but not in when, so the recent counts are a floor, and a kind none of whose pages gives a publication date reads undated. An event counts as online when its address or title says so (webinar, on demand, virtual or online summit); a conference, summit, trade show, expo or roadshow that does not say so is counted as a conference or event, which on a vendor's site is mostly in person. Read September 29, 2026.
Names read as TensorFlow
What the judge wrote, as written, with how often. The vendor table decides that these count as TensorFlow; a claim can dispute any of them.
TensorFlow (Google) 1
Follow TensorFlow
An email the morning each edition publishes: where this product moved, where it held, and by how much against the noise floor. One address, confirmed by a click; a stop link in every email.
Already following? Everything you follow, with a stop for each.
The company
TensorFlow is its own company.ShowHide
The company
TensorFlow is its own company.
ShowHideIn its own words
Stated by the vendor, not checked- Positioning
- An end-to-end open source machine learning platform for everyone.
- For
- everyone
- Customers named
- Spotify
- Not stated on the pages read
- Price, starting price, free plan or trial, integrations, certifications, hosting
What TensorFlow's own pages state, read September 28, 2026: tensorflow.org, tensorflow.org/datasets/api_docs/python/tfds/features/Text. A claimed page can correct any of them.
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 TensorFlow'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 TensorFlow, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.
What a new claim receivesHide what a new claim receives
A new claim receives the current edition's vendor brief for TensorFlow by email, built from the raw record of the edition. It shows:
- where TensorFlow is named, by buyer and by framing, and which cells hold its first choices;
- the claims the models make when they name it, ranked, with the strongest and the weakest quoted;
- its vocabulary against the segment leader's, and the pages the models cited;
- who was chosen in the answers that did not name TensorFlow, and every reason the record gives;
- a battlecard for each top rival: the head-to-head split, why they win, and the reservation quoted against them;
- one page of published figures cleared to show a buyer.