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Vertex AI logo
Vertex AI
Google
Llama logo
Llama
Meta Platforms
Head-to-head in this comparison
Advantages
Free trial available
Can run on-premise
Vendor is publicly listed — audited financial disclosure
Longest track record — vendor founded 1993
Free trial available
Vendor is publicly listed — audited financial disclosure
Largest vendor (183,000 employees)
Only one here with Multi-language
Free plan available
Can run on-premise
Vendor is publicly listed — audited financial disclosure
Only one here with Dashboards
Free trial available
Broadest feature coverage (9)
Drawbacks
Lacks Single sign-on (SSO), Role-based access, Audit log +3 more — offered by others here
No free plan
Narrowest feature scope (3)
Lacks Self-hosted — offered by others here
No free plan
Cloud only
Lacks Single sign-on (SSO), Role-based access, Audit log +3 more — offered by others here
No free trial
Lacks Self-hosted — offered by others here
No free plan
Cloud only
Smallest vendor (4,000 employees) — check support capacity
Least established — vendor founded 2013
Editorial assessment
Strengths
Optimized frameworks and microservices for NVIDIA GPUs
Enterprise support for open-source AI software stacks
Runs across public cloud, data center and edge
End-to-end ML and generative AI tooling
Access to Gemini and third-party models
Integrates with BigQuery and Google Cloud services
Open-weight models can be self-hosted and fine-tuned
Large ecosystem of tools, hosting providers and community
Range of model sizes for different hardware budgets
Unified lakehouse for data engineering and AI
Built on open formats like Delta Lake and Spark
Strong collaborative notebooks and ML tooling
Considerations
Value is tied to NVIDIA accelerated hardware
Subscription adds cost on top of infrastructure
Requires in-house ML and platform engineering skills
Complex for teams new to Google Cloud
Usage-based costs can escalate
Rapidly changing features and documentation
Community license has usage conditions to review
Self-hosting requires GPU infrastructure and ML skills
No vendor-managed support by default
Usage-based costs can be hard to predict
Requires data engineering expertise
Cluster tuning and governance need attention
Product & company facts
Deloitte alliance ✓ ✓ ✓ ✓
Rating — — — —
Starting price Price not listed Price not listed Free Price not listed
Pricing model Subscription Usage-based Free Usage-based
Free plan ✕ ✕ ✓ ✕
Free trial ✓ ✓ ✕ ✓
Open source ✕ ✕ ✕ ✕
Deployment Cloud (SaaS), On-premise, Hybrid Cloud (SaaS) Cloud (SaaS), On-premise, Hybrid Cloud (SaaS)
Platforms Linux Web Linux, Web Web
Turkish interface ✕ ✕ ✕ ✕
Target size Enterprise Small business, Mid-market, Enterprise Freelancer, Small business, Mid-market, Enterprise Mid-market, Enterprise
Industries served Technology, media & telecom, Automotive, Healthcare, Manufacturing & industrial, Cross-industry Retail & consumer, Banking & capital markets, Healthcare, Technology, media & telecom, Government & public sector, Cross-industry Technology, media & telecom, Banking & capital markets, Healthcare, Government & public sector, Cross-industry Banking & capital markets, Healthcare, Life sciences, Retail & consumer, Manufacturing & industrial, Cross-industry
Active users — — — —
Customers — — — —
Vendor employees 42,000 183,000 74,067 4,000
Headquarters Santa Clara, US Mountain View, US Menlo Park, US San Francisco, CA, US
Founded 1993 1998 2004 2013
Categories AI & ML Platforms AI & ML Platforms AI & ML Platforms Data Platforms & Warehousing, AI & ML Platforms
Features
AI features ✓ ✓ ✓ ✓
HIPAA — ✓ — ✓
ISO 27001 — ✓ — ✓
SOC 2 — ✓ — ✓
Self-hosted ✓ — ✓ —
API access ✓ ✓ ✓ ✓
Multi-language — — ✓ —
Dashboards — — — ✓
Audit log — ✓ — ✓
Role-based access — ✓ — ✓
Single sign-on (SSO) — ✓ — ✓

Feature marks are based on our curated data; “—” means not verified, not necessarily missing. Head-to-head points are derived from this data relative to the selected products; editorial points are curated summaries.

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