Small business▼−2Since September 2026: 2% → 0%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
0%from 2% in September 2026
Inside the floor by 9 pointsRank 12 → 28 of 131
1 category · Named, not rankedBigML
14Judge labels
1First choices
0Negative labels
7 / 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.
Standing
4 labels, too few to rank
A product needs 10 labels in a category before a share or quadrant is stated. BigML was named 4 times in ML platforms, where Azure Machine Learning led with 21%. The labels and the evidence are below, counted exactly.
By buyer segmentRead the same way at every buyer size.
Small business14 of 139
2%9 labels
under the label threshold
Mid-market25 of 107
0%4 labels
under the label threshold
Enterprisenot named
0%
No model named it for this buyer.
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 BigML 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 | 0% | 25 of 107 | 0% | 4 | under 10 labels · led by Azure Machine Learning at 21% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
Movement
Since September 2026, BigML held within the floor in its one category: no change cleared 11 points.
Best category · ML platforms · by segment
Mid-market=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
0%from 0% in September 2026
Inside the floor by 11 pointsRank 22 → 29 of 97
All categories · Mid-market
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| ML platforms | 0% | 0% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 22 → 25 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 BigML 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 BigML 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 | 0 | 0 | 0 |
| GPT-5.4 mini | 0 | 0 | 0 | 0 | 0 |
| Gemini 3.5 Flash | 0 | 0 | 0 | 0 | 0 |
| Perplexity Sonar | 0 | 0 | 1 | 0 | 1 |
| Grok 4.20 | 0 | 0 | 0 | 0 | 0 |
| Mistral Small | 0 | 1 | 1 | 0 | 2 |
| DeepSeek V4 Flash | 0 | 0 | 0 | 0 | 0 |
| Llama 4 Maverick | 0 | 0 | 0 | 0 | 0 |
| Qwen 3.7 Flash | 0 | 0 | 0 | 0 | 0 |
| Kimi K2 | 0 | 0 | 0 | 0 | 0 |
| GLM 4.7 FlashX | 0 | 0 | 0 | 0 | 0 |
| MiniMax M2.5 | 0 | 0 | 0 | 0 | 0 |
| GPT-6 Luna | 0 | 0 | 0 | 0 | 0 |
| Muse Glimmer 30B | 0 | 1 | 0 | 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
Direct3 labels1
Paraphrase0 labelsNone
Comparative3 labelsNone
Budget-constrained4 labelsNone
Scale-constrained0 labelsNone
Negative4 labels1not counted in share
First choiceAlternativeMentionNegative14 labels in all, every segment counted; 1 of the 2 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.
“Starts with a free tier and uses pay-per-prediction pricing” Mistral Small · ML platforms · budget prompt · alternative
“layer in BigML for simple AutoML and hosted predictions” Muse Glimmer 30B · ML platforms · budget 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 BigML, over the 14 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and BigML was named but was not.ShowHide
Named alongside
The products named in the same answers as BigML, over the 14 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and BigML 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 BigML. 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 14 of the 14 answers that named BigML and are not a share of its labels.
Domains cited
checkthat.ai7
g2.com7
it-ai-index.com7
learn.g2.com7
devopsschool.com6
dagshub.com5
appreviewlab.com4
spotsaas.com4
startupstash.com4
alphasoftware.com3
Fifty-four of the fifty-four domain citations in answers naming BigML came from somebody else's page.
Pages cited
Pages are listed as the models cited them.
Search and answers
bigml.com is not in Google's top ten for any of the category's searches. In the answers, BigML takes 0% of first choices and Azure Machine Learning takes 21%.ShowHide
Search and answers
bigml.com is not in Google's top ten for any of the category's searches. In the answers, BigML takes 0% 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
- 210 a month (“bigml”)
- AI search demand for its name, est.
- 4 a month
- Organic visits to its site
- about 568 a month
- Searches its site ranks for
- 143 · 9 in the top three
- Sites linking to it
- 2,222
- Paid Google search
- No ads found in the estimate; that does not mean it runs none
Ads on Google
None found in Google's ad transparency records for the US
In answers
This editionShare of first choices
0%
rank 25 of 107 in ML platforms
Segment leader
21%
Azure Machine Learning
- First choices
- 1 across its categories
- Named in
- 14 answers
- Its own site cited
- in 14 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 bigml.com
708
subdomains included
Content
701
counted in the table below
Documentation
0
Product · Integration
0 · 0
| Kind | Pages | Last 90 days | 2025-10 to 2026-09 | Latest | Categories named |
|---|---|---|---|---|---|
| Blog | 653 | 0 | 2026-03-16 | ML platforms | |
| Webinar or virtual event | 30 | 0 | 2021-12-01 | ||
| Conference or event | 9 | 0 | 2020-04-01 | ||
| Case study | 2 | 0 | 2018-05-01 | ||
| Report or ebook | 2 | 0 | 2021-02-01 | ||
| Comparison | 2 | 0 | 2013-09-01 | ||
| News or press | 2 | undated | |||
| Podcast or video | 1 | 0 | 2020-01-01 |
Most recent
- 2026-03-16Grading our 2026 oscars machine learning predictions blog
- 2026-03-12Predicting the 2026 oscar winners with machine learning blog
- 2026-03-0103 blog
- 2025-12-172025 a year of quality education and applied impact blog
- 2025-12-02Ml models automated easily find the best ml model for your data blog
- 2025-12-0112 blog
How it is countedHide how it is counted
Every page bigml.com 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.
Follow BigML
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
BigML is its own company.ShowHide
The company
BigML is its own company.
ShowHideIn its own words
Stated by the vendor, not checked- Positioning
- Machine Learning made beautifully simple for everyone
- For
- your business
- Price stated
- Get started with a 3-day FREE trial - FREE access to all BigML functionality. bigml.com
- Free plan or trial
- 3-day FREE trial bigml.com
- Not stated on the pages read
- Starting price, integrations, certifications, hosting, customers
What BigML's own pages state, read September 28, 2026: bigml.com. 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 BigML'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 BigML, 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 BigML by email, built from the raw record of the edition. It shows:
- where BigML 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 BigML, 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.