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Compare · LLM models & APIs

GPT VS Llama

As of 30 October 2026, Llama is named by 386 companies and GPT by 796; GPT skews to companies under 200 people (48% vs 45%), Llama to companies over 1,000 (34% vs 29%).

As of 30 October 2026 · refreshed daily · counts move as websites, DNS and career sites are re-read.

The website-and-DNS footprint is not comparable between a marketing suite and a CRM: GPT's script and mail records show on hundreds of thousands of small sites, Llama rarely leaves a trace outside its own apps. Compare on the job-posting numbers; use the footprint for reach.

GPT: 2–200 employees
48%
Llama: 2–200 employees
45%
GPT: 1,000+ employees
29%
Llama: 1,000+ employees
34%
Postings per company, 90 days
3.2 · 2.9
Website or DNS footprint
0 · 0
796companies name GPT
386companies name Llama
342name both
2,581 · 1,136postings in 90 days, GPT · Llama
02Side by side

Who chooses which

Share of each tool's companies in every segment. "Leans" marks a gap of more than two points.

By company size
SegmentGPTshareLlamashareLeans
Self-employed213%72%even
2-10 employees8010%4010%even
11-50 employees15419%6918%even
51-200 employees14919%6517%even
201-500 employees10914%4411%GPT
501-1000 employees547%298%even
1001-5000 employees9812%6717%Llama
5001-10000 employees354%195%even
10,001+ employees9612%4612%even
By industry
SegmentGPTshareLlamashareLeans
Technology & software44155%23561%Llama
Business & finance services16320%6918%GPT
Manufacturing & industry527%256%even
Media & content314%113%even
Commerce & trade223%51%even
Consumer services & leisure223%92%even
Public, community & associations172%92%even
Utilities & infrastructure122%103%even
Property & construction101%31%even
Health care91%31%even
Transport, logistics & rental71%31%even
Automotive51%21%even
By country
SegmentGPTshareLlamashareLeans
United States46358%23260%even
United Kingdom527%318%even
Germany476%123%GPT
India405%256%even
France243%103%even
Canada152%62%even
Netherlands132%41%even
Singapore132%113%even
Australia111%62%even
Belgium111%––outside top 12
Brazil81%––outside top 12
Spain81%72%even
Switzerland––51%outside top 12
United Arab Emirates––31%outside top 12
Postings by team (share of each tool's postings)
SegmentGPTshareLlamashareLeans
Data & AI1,35140%93264%Llama
Software engineering68620%20514%GPT
IT operations & business systems2447%463%GPT
Education & training1003%30%GPT
Sales863%161%even
Product, program & project management822%141%even
Engineering (non-software)632%201%even
Marketing & communications612%91%even
Design & UX481%40%even
Finance & accounting321%––outside top 12
General management & consulting291%222%even
Customer service & success251%70%even
Research and science––60%outside top 12
Cite this

Quote the sentence with the date and the link. The numbers change daily; the link always shows the current ones.

Llama is named by 386 companies in job postings and GPT by 796; 342 name both. (Breaknorm, 30 October 2026, https://breaknorm.co/compare/gpt-vs-llama)
How we know

Read from the source, not self-reported

Every number on this page can be traced to a page we crawled or a posting we read. Full methodology →

  • Job postingsRead hourly from career sites. A tool counts when the employer's own text names it as the team's system; both tools can count for one company.
  • Website and DNSScripts and embeds on the company's pages, plus SPF, DKIM, MX and CNAME records of its domain that point at the vendor.
  • SegmentsCountry, size and industry from the company profile built from its website.
  • Not a reviewNo ratings, prices or feature claims. For those, read the vendors.
FAQ

GPT vs Llama: questions

Which is more used, GPT or Llama?

By companies naming it in their own job postings, GPT (796) over Llama (386). By website-and-DNS footprint, Llama (0 vs 0), because its scripts and mail records sit on many small company sites.

Who chooses GPT?

48% of GPT companies have 2 to 200 employees, against 45% for Llama. 29% of GPT companies have over 1,000 employees, against 34% for Llama.

Do companies run both?

342 companies name both in their postings, usually GPT in marketing and Llama in sales, or during a migration.

Where do these numbers come from?

From the employer's own text in job postings read hourly from career sites, and from scripts found on company websites in our crawl. No vendor data, no surveys.

Companies and people

Get either list your way

The same data as a search, over MCP and the API, as bulk files, or pushed to you as it changes.

Every company on either tool,
with the person who owns it

Filter on GPT or Llama. Start free, no card.

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