Provider Dossier · Hyperscaler
Google Vertex AI
Enterprise-grade cloud integration, global regions and compliance breadth.
The Datum Index verdict
Recommended with confidence
Ranked No. 8 of 20 in our composite reputation index, and currently holding steady.
≈ 4.2 / 5 aggregate · 640 reviewer notes
Composite index · reviewed 10 July 2026
Findings
- Google Vertex AI holds a Datum Index composite reputation of 84 / 100 (≈ 4.2 / 5), ranked No. 8 of 20.
- It is a hyperscaler based in Mountain View, USA, founded 2021, offering open & proprietary model access.
- Its flagship offering is Gemini family, exposed through an OpenAI-compatible API.
- Indicative pricing is $1.25 / 1M tokens in / $5.00 / 1M tokens out (medium confidence).
- Reference throughput is ~111 tok/s with ~900 ms time-to-first-token; stated uptime is 99.9%.
Google Vertex AI enters our index at No. 8, a placement that reads as recommended with confidence. The composite rests on 640 reviewer notes gathered across the public record, and it is best understood not as a score out of ten but as a standing among peers. The trend line is flat: reviewer sentiment has held steady over recent quarters.
In its favour
Enterprise-grade cloud integration, global regions and compliance breadth.
On the numbers that flatter it: open & proprietary access, 4 named compliance attestations, and a reference throughput of ~111 tokens per second.
Points of concern
Console complexity and steeper onboarding than pure API shops.
The caveat a buyer should price in before committing production traffic. As with every entry, we weigh it against the field rather than against perfection.
Incident & Uptime Note
The record of being there
Google Vertex AI states an availability of 99.9%. Held over a full year, that headline implies on the order of 8.8 hours of cumulative unavailability — a useful sense of scale, though real incidents cluster rather than spread evenly, and a single bad afternoon can outweigh a quiet quarter.
Observatory Panel
Latency & throughput, in distribution
Monthly panels across the models Google Vertex AI serves medium
Gemini Pro
| Window | TTFT ms — mean · p50 · p90 | Throughput tok/s — mean · p50 · p90 | ||||
|---|---|---|---|---|---|---|
| May 2026 | ~1130 | ~960 | ~1820 | ~96 | ~104 | ~121 |
| June 2026 | ~1100 | ~960 | ~1860 | ~96 | ~104 | ~113 |
| July 2026 | ~1060 | ~900 | ~1520 | ~103 | ~111 | ~126 |
Gemini Flash
| Window | TTFT ms — mean · p50 · p90 | Throughput tok/s — mean · p50 · p90 | ||||
|---|---|---|---|---|---|---|
| May 2026 | ~640 | ~580 | ~1260 | ~170 | ~182 | ~194 |
| June 2026 | ~650 | ~610 | ~1320 | ~162 | ~174 | ~189 |
| July 2026 | ~670 | ~610 | ~1090 | ~164 | ~172 | ~199 |
Llama 3.3 70B
| Window | TTFT ms — mean · p50 · p90 | Throughput tok/s — mean · p50 · p90 | ||||
|---|---|---|---|---|---|---|
| May 2026 | ~860 | ~760 | ~1660 | ~121 | ~125 | ~149 |
| June 2026 | ~750 | ~700 | ~1110 | ~129 | ~134 | ~144 |
| July 2026 | ~720 | ~680 | ~1440 | ~132 | ~140 | ~151 |
All figures are single-stream, per-request rates as one user would see them — never aggregate accelerator throughput. Serving modes are not comparable with one another: shared serverless APIs batch many tenants per accelerator, dedicated and self-served deployments hand one tenant the whole card, and specialist silicon is a regime of its own. Read each figure within its mode.
No field returns on record for Google Vertex AI yet — the ledger above opens as soon as the first practitioner submission clears verification.
Key Facts
The record, in brief
| Category | Hyperscaler |
|---|---|
| Headquarters | Mountain View, USA |
| Founded | 2021 |
| Model access | Open & proprietary |
| Flagship / reference | Gemini family · Gemma / partner models |
| OpenAI-compatible API | Yes |
| Indicative price (in / out) | $1.25 / 1M tokens / $5.00 / 1M tokens medium |
| Reference throughput | ~111 tok/s |
| Reference TTFT | ~900 ms |
| Stated uptime | 99.9% |
| Compliance | SOC 2 Type II · ISO 27001 · GDPR · HIPAA |
| Composite reputation | 84 / 100 · ≈ 4.2 / 5 · 640 notes |
Reviewer Notes
What the field says
The 640 notes behind Google Vertex AI's standing are drawn from the accumulated public verdict of practitioners — the recurring praises and the recurring gripes — rather than from any single survey. Two themes dominate. Admirers return to one point above all: Enterprise-grade cloud integration, global regions and compliance breadth. Detractors return to another: Console complexity and steeper onboarding than pure API shops.
We publish neither individual reviews nor reviewer identities; the composite is an editorial synthesis, and the reviewer-note count is an order-of-magnitude indication of how much public signal informs it.
Related dossiers · see also
Peer entries in the same or adjacent category, for comparison against Google Vertex AI's standing.