MLflow VS Weights & Biases
As of 30 October 2026, Weights & Biases is named by 283 companies and MLflow by 1,327; MLflow skews to companies under 200 people (41% vs 51%), Weights & Biases to companies over 1,000 (23% vs 36%).
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: MLflow's script and mail records show on hundreds of thousands of small sites, Weights & Biases rarely leaves a trace outside its own apps. Compare on the job-posting numbers; use the footprint for reach.
- MLflow: 2–200 employees
- 41%
- Weights & Biases: 2–200 employees
- 51%
- MLflow: 1,000+ employees
- 36%
- Weights & Biases: 1,000+ employees
- 23%
- Postings per company, 90 days
- 2.5 · 2.1
- 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 | MLflow | share | Weights & Biases | share | Leans |
|---|---|---|---|---|---|
| Self-employed | 16 | 1% | 9 | 3% | even |
| 2-10 employees | 110 | 8% | 42 | 15% | Weights & Biases |
| 11-50 employees | 178 | 13% | 43 | 15% | even |
| 51-200 employees | 255 | 19% | 58 | 20% | even |
| 201-500 employees | 175 | 13% | 38 | 13% | even |
| 501-1000 employees | 121 | 9% | 28 | 10% | even |
| 1001-5000 employees | 212 | 16% | 41 | 14% | even |
| 5001-10000 employees | 68 | 5% | 9 | 3% | even |
| 10,001+ employees | 192 | 14% | 15 | 5% | MLflow |
| Segment | MLflow | share | Weights & Biases | share | Leans |
|---|---|---|---|---|---|
| Technology & software | 657 | 50% | 135 | 48% | even |
| Business & finance services | 277 | 21% | 47 | 17% | MLflow |
| Manufacturing & industry | 139 | 10% | 36 | 13% | Weights & Biases |
| Media & content | 48 | 4% | 16 | 6% | Weights & Biases |
| Commerce & trade | 40 | 3% | 5 | 2% | even |
| Public, community & associations | 39 | 3% | 13 | 5% | even |
| Utilities & infrastructure | 29 | 2% | 2 | 1% | even |
| Consumer services & leisure | 25 | 2% | 12 | 4% | Weights & Biases |
| Transport, logistics & rental | 18 | 1% | 8 | 3% | even |
| Health care | 17 | 1% | 3 | 1% | even |
| Property & construction | 16 | 1% | 3 | 1% | even |
| Automotive | 12 | 1% | 2 | 1% | even |
| Segment | MLflow | share | Weights & Biases | share | Leans |
|---|---|---|---|---|---|
| United States | 791 | 60% | 196 | 69% | Weights & Biases |
| United Kingdom | 100 | 8% | 18 | 6% | even |
| Germany | 58 | 4% | 10 | 4% | even |
| France | 50 | 4% | 6 | 2% | even |
| Canada | 39 | 3% | 9 | 3% | even |
| India | 37 | 3% | 12 | 4% | even |
| Netherlands | 28 | 2% | – | – | outside top 12 |
| Australia | 21 | 2% | – | – | outside top 12 |
| Poland | 18 | 1% | 2 | 1% | even |
| Singapore | 15 | 1% | 5 | 2% | even |
| Brazil | 12 | 1% | – | – | outside top 12 |
| Switzerland | 11 | 1% | 2 | 1% | even |
| United Arab Emirates | – | – | 3 | 1% | outside top 12 |
| Ireland | – | – | 2 | 1% | outside top 12 |
| Italy | – | – | 2 | 1% | outside top 12 |
| Segment | MLflow | share | Weights & Biases | share | Leans |
|---|---|---|---|---|---|
| Data & AI | 3,206 | 74% | 593 | 69% | MLflow |
| Software engineering | 421 | 10% | 86 | 10% | even |
| IT operations & business systems | 149 | 3% | 31 | 4% | even |
| Product, program & project management | 50 | 1% | 11 | 1% | even |
| Sales | 41 | 1% | 18 | 2% | even |
| General management & consulting | 31 | 1% | 5 | 1% | even |
| Engineering (non-software) | 20 | 0% | 4 | 0% | even |
| Research and science | 12 | 0% | 4 | 0% | even |
| Legal, compliance & risk | 10 | 0% | 7 | 1% | even |
| Finance & accounting | 7 | 0% | 4 | 0% | even |
| Marketing & communications | 7 | 0% | – | – | outside top 12 |
| Logistics warehouse and transport | 5 | 0% | – | – | outside top 12 |
| Education & training | – | – | 3 | 0% | outside top 12 |
| Administration & office | – | – | 1 | 0% | outside top 12 |
The companies behind each column
Companies using MLflow →
Companies using Weights & Biases →
mlops platforms ranked →
Quote the sentence with the date and the link. The numbers change daily; the link always shows the current ones.
Weights & Biases is named by 283 companies in job postings and MLflow by 1,327; 327 name both. (Breaknorm, 30 October 2026, https://breaknorm.co/compare/mlflow-vs-weights-and-biases)
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.
MLflow vs Weights & Biases: questions
Which is more used, MLflow or Weights & Biases?
By companies naming it in their own job postings, MLflow (1,327) over Weights & Biases (283). By website-and-DNS footprint, Weights & Biases (0 vs 0), because its scripts and mail records sit on many small company sites.
Who chooses MLflow?
41% of MLflow companies have 2 to 200 employees, against 51% for Weights & Biases. 36% of MLflow companies have over 1,000 employees, against 23% for Weights & Biases.
Do companies run both?
327 companies name both in their postings, usually MLflow in marketing and Weights & Biases 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.
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 MLflow or Weights & Biases. Start free, no card.