LiteLLM VS Text Generation Inference
As of 30 October 2026, Text Generation Inference is named by 108 companies and LiteLLM by 130; LiteLLM skews to companies under 200 people (31% vs 50%), Text Generation Inference to companies over 1,000 (25% vs 34%).
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: LiteLLM's script and mail records show on hundreds of thousands of small sites, Text Generation Inference rarely leaves a trace outside its own apps. Compare on the job-posting numbers; use the footprint for reach.
- LiteLLM: 2–200 employees
- 31%
- Text Generation Inference: 2–200 employees
- 50%
- LiteLLM: 1,000+ employees
- 34%
- Text Generation Inference: 1,000+ employees
- 25%
- Postings per company, 90 days
- 2.6 · 2.8
- Website or DNS footprint
- 0 · 0
Who chooses which
Share of each tool's companies in every segment. "Leans" marks a gap of more than two points.
| Segment | LiteLLM | share | Text Generation Inference | share | Leans |
|---|---|---|---|---|---|
| 2-10 employees | 6 | 5% | 14 | 13% | Text Generation Inference |
| 11-50 employees | 13 | 10% | 19 | 18% | Text Generation Inference |
| 51-200 employees | 21 | 16% | 21 | 19% | Text Generation Inference |
| 201-500 employees | 24 | 18% | 17 | 16% | LiteLLM |
| 501-1000 employees | 22 | 17% | 8 | 7% | LiteLLM |
| 1001-5000 employees | 26 | 20% | 13 | 12% | LiteLLM |
| 5001-10000 employees | 9 | 7% | 7 | 6% | even |
| 10,001+ employees | 9 | 7% | 7 | 6% | even |
| Self-employed | – | – | 2 | 2% | outside top 12 |
| Segment | LiteLLM | share | Text Generation Inference | share | Leans |
|---|---|---|---|---|---|
| Technology & software | 63 | 48% | 67 | 62% | Text Generation Inference |
| Business & finance services | 24 | 18% | 14 | 13% | LiteLLM |
| Media & content | 12 | 9% | 3 | 3% | LiteLLM |
| Manufacturing & industry | 7 | 5% | 11 | 10% | Text Generation Inference |
| Utilities & infrastructure | 6 | 5% | 2 | 2% | LiteLLM |
| Commerce & trade | 4 | 3% | – | – | outside top 12 |
| Public, community & associations | 4 | 3% | 5 | 5% | even |
| Consumer services & leisure | 4 | 3% | 3 | 3% | even |
| Transport, logistics & rental | 3 | 2% | 1 | 1% | even |
| Hospitality & travel | 2 | 2% | – | – | outside top 12 |
| Automotive | 1 | 1% | – | – | outside top 12 |
| Health care | – | – | 1 | 1% | outside top 12 |
| Property & construction | – | – | 1 | 1% | outside top 12 |
| Segment | LiteLLM | share | Text Generation Inference | share | Leans |
|---|---|---|---|---|---|
| United States | 76 | 58% | 70 | 65% | Text Generation Inference |
| France | 8 | 6% | 2 | 2% | LiteLLM |
| Germany | 7 | 5% | – | – | outside top 12 |
| United Kingdom | 7 | 5% | 12 | 11% | Text Generation Inference |
| Australia | 5 | 4% | 1 | 1% | LiteLLM |
| Austria | 2 | 2% | – | – | outside top 12 |
| Brazil | 2 | 2% | 4 | 4% | Text Generation Inference |
| Canada | 2 | 2% | 2 | 2% | even |
| Spain | 2 | 2% | 2 | 2% | even |
| Finland | 2 | 2% | – | – | outside top 12 |
| Netherlands | 2 | 2% | – | – | outside top 12 |
| Poland | 2 | 2% | – | – | outside top 12 |
| India | – | – | 3 | 3% | outside top 12 |
| Singapore | – | – | 2 | 2% | outside top 12 |
| United Arab Emirates | – | – | 1 | 1% | outside top 12 |
| Switzerland | – | – | 1 | 1% | outside top 12 |
| Cyprus | – | – | 1 | 1% | outside top 12 |
| Segment | LiteLLM | share | Text Generation Inference | share | Leans |
|---|---|---|---|---|---|
| Data & AI | 213 | 49% | 216 | 55% | Text Generation Inference |
| Software engineering | 134 | 31% | 65 | 17% | LiteLLM |
| IT operations & business systems | 19 | 4% | 3 | 1% | LiteLLM |
| Customer service & success | 8 | 2% | 2 | 1% | even |
| Sales | 8 | 2% | 9 | 2% | even |
| Product, program & project management | 6 | 1% | 1 | 0% | even |
| Engineering (non-software) | 3 | 1% | 4 | 1% | even |
| Design & UX | 1 | 0% | – | – | outside top 12 |
| Marketing & communications | – | – | 36 | 9% | outside top 12 |
| Manufacturing and production | – | – | 10 | 3% | outside top 12 |
| Business development & strategy | – | – | 3 | 1% | outside top 12 |
| General management & consulting | – | – | 2 | 1% | outside top 12 |
| Human resources | – | – | 1 | 0% | outside top 12 |
The companies behind each column
Companies using LiteLLM →
Companies using Text Generation Inference →
model serving gateways ranked →
Quote the sentence with the date and the link. The numbers change daily; the link always shows the current ones.
Text Generation Inference is named by 108 companies in job postings and LiteLLM by 130; 12 name both. (Breaknorm, 30 October 2026, https://breaknorm.co/compare/litellm-vs-text-generation-inference)
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.
LiteLLM vs Text Generation Inference: questions
Which is more used, LiteLLM or Text Generation Inference?
By companies naming it in their own job postings, LiteLLM (130) over Text Generation Inference (108). By website-and-DNS footprint, Text Generation Inference (0 vs 0), because its scripts and mail records sit on many small company sites.
Who chooses LiteLLM?
31% of LiteLLM companies have 2 to 200 employees, against 50% for Text Generation Inference. 34% of LiteLLM companies have over 1,000 employees, against 25% for Text Generation Inference.
Do companies run both?
12 companies name both in their postings, usually LiteLLM in marketing and Text Generation Inference 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.
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