GTM AI Index
Index Vendors › Orb · September 2026 Edition
1 category · Named, not ranked

Orb

17Judge labels
0First choices
2Negative labels
9 of 12Models named it
1Category
September 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-09-16.3, every buyer segment counted.
Standing
7 labels, too few to rank
A product needs 10 labels in a category before a share or quadrant is stated. Orb was named 7 times in Billing, where Chargebee led with 58%. The labels and the evidence are below, counted exactly.
By buyer segmentRead the same way at every buyer size.
In billing · 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 Orb 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.
CategoryFunctionShareRankNegative rateLabelsQuadrant
Billing and subscription managementRevenue operations0%15 of 570%7under 10 labels · led by Chargebee at 58%

Movement

This is the first edition on this tier, so no move can be computed for Orb yet. The next is due October 1, 2026. 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 Orb across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.
ModelFirst choiceAlternativeMentionNegativeLabels
Claude Haiku 4.500000
GPT-5.4 mini00000
Gemini 3.5 Flash02002
Perplexity Sonar00000
Grok 4.1 Fast00000
Mistral Small01001
DeepSeek V4 Flash00101
Llama 4 Maverick00000
Qwen 3.7 Flash00101
Kimi K200000
GLM 4.7 FlashX00000
MiniMax M2.501102

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 labelsNone
Paraphrase1 labelNone
Comparative9 labelsNone
Budget-constrained1 labelNone
Scale-constrained0 labelsNone
Negative3 labelsNone
First choiceAlternativeMentionNegative17 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.

“Best for: AI companies and usage-based pricing with complex consumption models” Mistral Small · Billing · comparative prompt · alternative
“Metronome and Orb are purpose-built modern metering and billing engines.” Gemini 3.5 Flash · Billing · direct prompt · alternative
“Usage-based models: Look at Metronome or Orb specifically” MiniMax M2.5 · Billing · negative prompt · alternative
“Orb provides phenomenal real-time developer ergonomics” Gemini 3.5 Flash · Billing · 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 Orb, over the 17 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Orb was named but was not.
ProductSame answerTook the first choice insteadHead to head
Chargebee17 of 175Not in the top three
Stripe Billing16 of 174Not in the top three
Zuora14 of 177Not in the top three
Metronome12 of 170Not in the top three
Recurly12 of 170Not in the top three
Maxio11 of 170Not in the top three
Paddle11 of 170Not in the top three
BillingPlatform5 of 170Not in the top three
FastSpring4 of 170Not in the top three
Lago4 of 170Not 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 Orb. 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 3 of the 17 answers that named Orb and are not a share of its labels.

Domains cited

solidgate.com3
whop.com3
younium.com3
connectpay.com2
hyperline.co2
learn.g2.com2
upflow.io2
withorb.com2
zoneandco.com2
billingplatform.com1

No domain is on file for Orb, so its own site is not marked.

Pages cited

Pages are listed as the models cited 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 Orb'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 Orb, 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 the vendor's own domain 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.