vLLM Inference Engine users list

Email list of companies using vLLM Inference Engine

Q: How many companies use vLLM Inference Engine?

Data InfoMetrix tracks 3,007 companies using vLLM Inference Engine, with 13,599 verified contacts at those accounts as of October 2026. The largest groups are AI Platforms, Enterprise IT and Cloud Providers. Counts are estimates from our database and market research, so ask us for a live count for your exact criteria.

Q: Who buys and manages vLLM Inference Engine inside a company?

vLLM Inference Engine is usually owned by Open-Source LLM Inference Serving. Decision-makers include CTO, VP of Infrastructure and Head of AI Research; ML Infrastructure Lead and HPC Engineer Lead shape the choice, and ML Engineers and Research Engineers use it day to day. Our vLLM Inference Engine list can include any of these roles.

Q: Which vLLM Inference Engine products or editions can I target?

You can target accounts by the vLLM Inference Engine products they run, including vLLM (Open Source), vLLM OpenAI-Compatible Server, vLLM on Kubernetes (llm-d), Red Hat AI Inference Server and vLLM Production Stack. Tell us which edition or module matters and we filter the list to those accounts.

Q: What other software do vLLM Inference Engine customers use?

vLLM Inference Engine customers commonly also run Kubernetes, Hugging Face, NVIDIA, Ray and Prometheus. We can filter any list by this kind of stack overlap.

Q: What are the main alternatives to vLLM Inference Engine?

The main alternatives to vLLM Inference Engine are TensorRT-LLM, SGLang and Text Generation Inference. We also keep verified user lists for TensorRT-LLM, which is useful for competitive displacement campaigns.

Q: When are vLLM Inference Engine customers most likely to buy?

Buying triggers we track for vLLM Inference Engine accounts include Self-hosted LLM rollout, GPU cluster expansion, move from API to open models and inference cost review. A common pain point is GPU cost and availability: compute is the biggest AI budget line.

Q: Can Data InfoMetrix deliver a free sample vLLM contact list before ordering?

Yes. Data InfoMetrix delivers a complimentary 10-record sample tailored to your target vLLM criteria—including target job titles, company size, and region—delivered within one business day with no obligation.

Q: How does Data InfoMetrix guarantee email deliverability for vLLM contacts?

Data InfoMetrix provides a 99% email deliverability guarantee on all vLLM datasets. Every contact record undergoes real-time email verification within a 30 to 45-day refresh cycle, backed by a 1:1 hard bounce replacement policy for 30 days after delivery.

Reach ML infrastructure and AI platform teams serving open-weight models with vLLM for high-throughput inference.

3,007+Companies

13,599+Contacts

Updated Oct 7, 2026GDPR · CCPA99% accuracy

See sample data

Free vLLM Inference Engine count + 10 sample records

3,007+ companies · 13,599+ contacts available

✓Exact count for your titles, regions and company size
✓10 verified sample records to check quality
✓Price quote within 1 business day

Trusted by B2B and enterprise revenue teams

How many companies use vLLM Inference Engine?

Data InfoMetrix tracks 3,007+ companies running vLLM Inference Engine as of October 2026, with 13,599+ verified contacts at those accounts. The largest groups are AI Platforms, Enterprise IT and Cloud Providers. Buying decisions usually sit with the CTO, VP of Infrastructure and Head of AI Research. Counts are estimates built from technology footprint scans, job-post signals and partner directories, checked by our research team. How we count

Tracked accounts3,007+

Organizations detected running vLLM Inference Engine.

Verified contacts13,599+

Direct emails and phone dials for decision-makers.

Primary personasHead of ML Infrastructure, Staff ML Engineer, CTO

Full buying committee mapped.

Deliverability SLA99%

SMTP-verified, with 1:1 replacement of any email that hard bounces within 30 days.

Data specification · Updated Q4 2026

Technology category	AI Infrastructure & LLM Ops
Tracked organizations	3,007+ verified accounts worldwide
Decision-maker contacts	13,599+ records with emails, mobile and direct dials
Key roles	Head of ML Infrastructure, Staff ML Engineer, CTO, platform administrators, IT directors, procurement
Geography	180+ countries · country-by-country counts on request
Verification	DNS and script telemetry, 5-stage SMTP handshake, manual research
Refresh cadence	Continuous, 30–45 day maximum record age at delivery
Compliance	GDPR, CAN-SPAM, CCPA and CASL
Delivery	24–48 hours as CSV, XLSX or CRM API

Editorial & verification

Researched by the Data InfoMetrix research team. Counts updated October 2026.

How we count and verify data

Size your vLLM Inference Engine audience

Pick a region, company size and buying role to estimate how many accounts and contacts you can reach.

Region

Company size

Buying role

Estimated segment✓ 99% SLA

3,007+Target accounts

13,599+Direct contacts

Decision-makers35%

Influencers45%

End users20%

Estimates from our current vLLM Inference Engine dataset. Exact counts come with your quote.

Reach the whole buying committee

A vLLM Inference Engine account is not one contact. We map the people who evaluate, buy, run and use it across Open-Source LLM Inference Serving.

Decision-makersC-suite & sponsors

CTOVP of InfrastructureHead of AI ResearchCEO (AI Startup)

Influencers & adminsEvaluate & configure

ML Infrastructure LeadHPC Engineer LeadPlatform Engineering ManagerFinOps Lead

End usersRun it every day

ML EngineersResearch EngineersInfrastructure EngineersData Scientists

These are examples. We build records for any department, seniority or custom title.

See exactly what you get

Every record carries 60+ fields, from verified email, direct dial and LinkedIn to full postal address, vLLM Inference Engine edition, coexisting stack and intent.

Contact	Buying role	Work email	Direct dial	Company phone	Fax	LinkedIn profile	Company	LinkedIn company page	Industry	Address 1	Address 2	City	State	ZIP code	Country	vLLM Inference Engine footprint	Intent	Status
ATDr. Aris ThorneChief AI Officer (CAIO)	Decision Maker	a.th**@cogniti*****.io	+1 (415) 55*-**	+1 (415) 55*-**	+1 (415) 55*-**	linkedin.com/in/a*s-th******	CognitiveScale Enterprise AI Systems Inc.	linkedin.com/company/cognitivescale-ai	Applied AI & Autonomous Agent Platforms	100 Pine St	Ste 2400	San Francisco	CA	94111	United States	vLLM Inference Engine Enterprise AI Infrastructure & Cloud Cluster	High	✓ Verified 2026
NSNaveen SwaminathanVP of AI Engineering & LLMOps Architecture	Decision Maker	n.swa***@synapse*****.com	+1 (617) 55*-**	+1 (617) 55*-**	+1 (617) 55*-**	linkedin.com/in/n*en-swa*******	Synapse Biotech AI Discovery Inc.	linkedin.com/company/synapse-biotech-ai	Biotechnology & Computational Drug Discovery	500 Technology Square	—	Cambridge	MA	02139	United States	vLLM Inference Engine LLM Observability, Evaluation & Prompt Tracing	High	✓ Verified 2026
HLHannah LindqvistHead of Semantic Search & Vector Retrieval	Decision Maker	h.lin**@stockh***.se	+46 (8) 55*-**	+46 (8) 55*-**	+46 (8) 55*-**	linkedin.com/in/h*ah-li*******	Stockholm Neural Search Solutions AB	linkedin.com/company/stockholm-neural-search	E-Commerce Semantic Search & Discovery	Sveavägen 44	—	Stockholm	Stockholm County	111 34	Sweden	vLLM Inference Engine Vector Database & Approximate Nearest Neighbor Indexing	High	✓ Verified 2026
CVCameron VanceLead Machine Learning Infrastructure Architect	Influencer	c.va**@apexfin****.com	+1 (212) 55*-**	+1 (212) 55*-**	+1 (212) 55*-**	linkedin.com/in/c*ron-v*******	Apex FinTech Neural Analytics LLC	linkedin.com/company/apex-fintech-neural	Financial Market Prediction & Fraud Telemetry	1301 Ave of the Americas	—	New York	NY	10019	United States	vLLM Inference Engine High-Throughput Inference & Speculative Decoding	High	✓ Verified 2026
ERDr. Evelyn RousseauDirector of Applied NLP & RAG Systems	Influencer	e.rou**@parishe****.fr	+33 (1) 45*-**	+33 (1) 45*-**	+33 (1) 45*-**	linkedin.com/in/e*yn-ro*******	Paris Clinical Intelligence Labs SAS	linkedin.com/company/paris-clinical-ai	Clinical Decision Support & Biomedical NLP	15 Boulevard Saint-Germain	—	Paris	Île-de-France	75005	France	vLLM Inference Engine Enterprise RAG Pipeline & Semantic Knowledge Search	Medium	✓ Verified 2026
DCDarren CrossHead of Developer Experience & AI Tooling	Decision Maker	d.cr**@acceler*****.com	+1 (206) 55*-**	+1 (206) 55*-**	+1 (206) 55*-**	linkedin.com/in/d*en-cr******	Accelerate Cloud Engineering Corp	linkedin.com/company/accelerate-cloud-eng	Enterprise Cloud Systems & Developer Platforms	1201 3rd Ave	Ste 2200	Seattle	WA	98101	United States	vLLM Inference Engine AI Code Generation & Developer Productivity Platform	High	✓ Verified 2026
AMAlistair MontgomeryLead AI Safety & Guardrails Engineer	Practitioner	a.mon**@edinburghf*******.uk	+44 (131) 55*-**	+44 (131) 55*-**	+44 (131) 55*-**	linkedin.com/in/a*air-mo*******	Edinburgh Quantitative Systems Ltd	linkedin.com/company/edinburgh-quant-sys	Automated Financial Advisory & Wealth Management	1 Lochside Ave	—	Edinburgh	Midlothian	EH12 9DJ	United Kingdom	vLLM Inference Engine Agentic Workflow Execution & Guardrail Enforcement	Medium	✓ Verified 2026
KMKenichi MurataSenior Distributed AI Platform Engineer	Practitioner	k.mu**@kyotone*****.jp	+81 (75) 55*-**	+81 (75) 55*-**	+81 (75) 55*-**	linkedin.com/in/k*chi-m*******	Kyoto Neural Robotics Systems KK	linkedin.com/company/kyoto-neural-robotics	Robotics & Autonomous Machine Vision	Kyoto Research Park	Bldg 4	Kyoto	Kyoto Prefecture	600-8815	Japan	vLLM Inference Engine Model Training & Distributed GPU Optimization	High	✓ Verified 2026

Illustrative rows showing 20 of 60+ fields. Full records are unmasked.

We deliver 60+ data fields per record, including intent data. The sample shows a selection only. Tell us which fields you need, including any that aren't listed here, and we'll add them to your list.

Also available:Seniority & departmentJob functionTenure in roleEmployee countAnnual revenueSIC & NAICS codesParent companyWebsite & domainProduct editionContract & renewal timingIntent topics & scoreEmail verification date

How we prove an account runs vLLM Inference Engine

No scraped résumés or stale directories. Three layers confirm a live installation before a contact reaches your list. Read our verification protocol

Pillar 1 · Telemetry

Live DNS & script signals

We inspect response headers, DNS MX and CNAME records and live JavaScript bundles to confirm a running vLLM Inference Engine instance.

DNS · CNAME · MX recordsHTTP headers · JS bundles✓ Verified against live infrastructure

Pillar 2 · Operational intent

90-day hiring signals

We track job requisitions that ask for vLLM Inference Engine skills, which shows ongoing budget and headcount.

Now hiringvLLM Inference Engine Administrator

Now hiringvLLM Inference Engine Architect

Now hiringvLLM Inference Engine Engineer

Pillar 3 · Human & mailbox QA

Pre-delivery SMTP handshake

Each email is tested against the destination mail server, and titles are checked against current company rosters.

SMTP check ✓LinkedIn match ✓Title verified ✓

✓ Deliverable inbox and current role

Deliverability SLA

<3%

Maximum bounce rate, or we replace the contacts. Your sender reputation stays clean.

1:1 hard bounce replacement

Every email that hard-bounces within 30 days of delivery is replaced free, record for record.

24-hour pre-delivery ping

Live SMTP and MX checks right before we send your file.

Instant CRM import

Clean CSV or XLSX, ready for one-click import.

Ready for your outbound stack

Imports straight into the tools you use.

What are you trying to do?

Each campaign needs a different data strategy. Pick your goal to see how we build the audience.

Find companies on rival platforms and reach the people evaluating a move to, or away from, vLLM Inference Engine.

Conquesting playbook

Pitch integrations, add-ons and complementary tools to companies already running vLLM Inference Engine.

Ecosystem playbook

Build account lists around vLLM Inference Engine deployment scale and engage the full committee across departments.

ABM playbook

Conquesting audienceSample

TensorRT-LLM

SGLang

Text Generation Inference

→

vLLM Inference Engine

Know the stack around every account

vLLM Inference Engine rarely runs alone. Every record is tagged with the tools detected alongside it, so you can segment by complementary stacks.

Ray

Open the coexistence matrix

What vLLM Inference Engine customers look like

Anonymised profiles of companies in our vLLM Inference Engine dataset of 3,007+ accounts. Named accounts are shared in your free sample, never on a public page.

vLLM Inference Engine account profiles · anonymised

Company size	Industry	Country	Employees	Revenue
Mid-market	Cloud Providers	United Kingdom	200–999	$50M–$250M
Enterprise	Research Labs	United States	5,000+	$1B+
Upper mid-market	AI Platforms	Canada	1,000–4,999	$250M–$1B
SMB	Enterprise IT	Germany	50–199	$10M–$50M
Enterprise	Cloud Providers	United States	10,000+	$5B+
Mid-market	Research Labs	Australia	500–999	$100M–$250M
Mid-market	AI Platforms	United States	200–999	$50M–$250M
Enterprise	Enterprise IT	United States	5,000+	$1B+

Markets we cover

United States

India

United Kingdom

Canada

Germany

Australia

Singapore

France

New Zealand

Netherlands

Plus 170 more countries. Ask for a country-by-country count of vLLM Inference Engine accounts and we'll include it with your free sample.

Build the list your way

Every list is assembled from source to your product tier, job function, geography and revenue band. Nothing is a fixed export.

Editions & modules

Filter by what they actually run.

+vLLM (Open Source)+vLLM OpenAI-Compatible Server+vLLM on Kubernetes (llm-d)+Red Hat AI Inference Server+vLLM Production Stack

Firmographics

Match revenue, size and industry.

+Industry+$1M–$10B+ revenue+Headcount+Ownership & funding+HQ & branches

Geography

Target any territory.

+US & Canada+US states+UK, DACH, Nordics+APAC & ANZ+Metro clusters

Need multi-attribute segments? Open the Audience Builder

What vLLM Inference Engine teams are struggling with

Know the friction before you reach out, and position your product where it matters.

Friction 1

GPU cost and availability

ImpactCompute is the biggest AI budget line.

OpportunityOffer capacity brokering and FinOps for AI.

Friction 2

Serving latency at scale

ImpactUsers notice slow responses.

OpportunityPitch inference optimisation services.

Friction 3

Operating open models

ImpactSelf-hosting needs MLOps skills.

OpportunityOffer managed inference and MLOps.

Intent triggers we track

✓Self-hosted LLM rollout

✓GPU cluster expansion

✓Move from API to open models

✓Inference cost review

“When you talk to companies who already use Snowflake and AWS about a native integration, the conversion rate skyrockets. Data InfoMetrix gave us the exact user list we needed.”

Director of Growth, a data integration companyName withheld at the client's request

Read the 6.8% Response case study

vLLM Inference Engine list questions, answered

How many companies use vLLM Inference Engine?

Data InfoMetrix tracks 3,007 companies using vLLM Inference Engine, with 13,599 verified contacts at those accounts as of October 2026. The largest groups are AI Platforms, Enterprise IT and Cloud Providers. Counts are estimates from our database and market research, so ask us for a live count for your exact criteria.

Who buys and manages vLLM Inference Engine inside a company?

vLLM Inference Engine is usually owned by Open-Source LLM Inference Serving. Decision-makers include CTO, VP of Infrastructure and Head of AI Research; ML Infrastructure Lead and HPC Engineer Lead shape the choice, and ML Engineers and Research Engineers use it day to day. Our vLLM Inference Engine list can include any of these roles.

Which vLLM Inference Engine products or editions can I target?

You can target accounts by the vLLM Inference Engine products they run, including vLLM (Open Source), vLLM OpenAI-Compatible Server, vLLM on Kubernetes (llm-d), Red Hat AI Inference Server and vLLM Production Stack. Tell us which edition or module matters and we filter the list to those accounts.

What other software do vLLM Inference Engine customers use?

vLLM Inference Engine customers commonly also run Kubernetes, Hugging Face, NVIDIA, Ray and Prometheus. We can filter any list by this kind of stack overlap.

What are the main alternatives to vLLM Inference Engine?

The main alternatives to vLLM Inference Engine are TensorRT-LLM, SGLang and Text Generation Inference. We also keep verified user lists for TensorRT-LLM, which is useful for competitive displacement campaigns.

When are vLLM Inference Engine customers most likely to buy?

Buying triggers we track for vLLM Inference Engine accounts include Self-hosted LLM rollout, GPU cluster expansion, move from API to open models and inference cost review. A common pain point is GPU cost and availability: compute is the biggest AI budget line.

Can Data InfoMetrix deliver a free sample vLLM contact list before ordering?

Yes. Data InfoMetrix delivers a complimentary 10-record sample tailored to your target vLLM criteria—including target job titles, company size, and region—delivered within one business day with no obligation.

How does Data InfoMetrix guarantee email deliverability for vLLM contacts?

Data InfoMetrix provides a 99% email deliverability guarantee on all vLLM datasets. Every contact record undergoes real-time email verification within a 30 to 45-day refresh cycle, backed by a 1:1 hard bounce replacement policy for 30 days after delivery.

Sourcing and compliance. Business contacts come from public company sources, professional directories and opt-in publishing partners, then go through SMTP verification and human review. Lists are for B2B outreach: include an unsubscribe link and honour opt-outs (CAN-SPAM), and have a lawful basis such as legitimate interest when you email people in the EU or UK (GDPR). Read how we source and verify data