Google Vertex AI via VerticalAPI
Vertex-hosted Gemini, Claude and Llama via VerticalAPI's OpenAI-compatible endpoint. BYOK with a GCP service account, zero markup, region-pinned inference.
Google Vertex AI models routed by VerticalAPI
Pass the model ID below as model in any OpenAI-compatible request. New Google Vertex AI models are typically supported within 24h of release.
| Model ID | Name | Context | Pricing (provider) |
|---|---|---|---|
gemini-2.5-pro |
Gemini 2.5 Pro (Vertex) | 2M | Vertex pricing |
claude-sonnet-4-5@vertex |
Claude Sonnet 4.5 (Vertex) | 200K | Anthropic-on-Vertex pricing |
llama-3.3-70b@vertex |
Llama 3.3 70B (Vertex) | 128K | Vertex Llama pricing |
Pricing reflects Google Vertex AI's rates — you pay Google Vertex AI directly. VerticalAPI adds zero markup on tokens.
5-line Google Vertex AI call via VerticalAPI
Drop-in replacement for the OpenAI SDK. Works with the OpenAI Python client, Node, Go, curl — anything that speaks HTTP.
from openai import OpenAI client = OpenAI( base_url="https://api.verticalapi.com/v1", api_key="vapi_...", default_headers={"X-Provider-Key": "GCP service-ac..."} ) response = client.chat.completions.create( model="gemini-2.5-pro", # Google Vertex AI messages=[{"role": "user", "content": "Hello"}] ) print(response.choices[0].message.content)
Four reasons developers route Google Vertex AI through us
Zero token markup
You pay Google Vertex AI directly with your own key. VerticalAPI's revenue is the gateway subscription, not a tax on your tokens.
One key, every provider
Google Vertex AI alongside OpenAI, Anthropic, Gemini and 12 more — same OpenAI-compatible endpoint, same SDK, switchable per-request.
Latency & cost monitoring
Per-request token counts, p50/p95 latency and cost dashboards out of the box. Compare Google Vertex AI to other providers on identical prompts.
Observability built in
Every Google Vertex AI call gets a trace ID, replayable payload and audit log entry. Wire to Datadog or Sentry via OpenTelemetry.
Where Google Vertex AI shines
Frequently asked questions
What is Vertex AI and what models do they offer?
Vertex AI is Google Cloud's managed AI/ML platform. The 2026 model garden includes Gemini 2.5 Pro and Flash, Anthropic Claude 4.5 (via Anthropic-on-Vertex), Meta Llama 3.3, Mistral Large, Imagen 3 for images, Veo 2 for video, Chirp 3 for speech, plus custom-tuned Gemini and open-source models on Model Garden. Vertex adds MLOps tooling, agent builders, RAG (Vertex Search) and evaluation.
How much does Vertex AI cost in 2026?
Gemini 2.5 Pro is $1.25 per 1M input tokens (up to 200K) and $10 per 1M output. Gemini 2.5 Flash is around $0.30/$2.50. Claude Sonnet 4.5 on Vertex matches Anthropic's $3/$15. Llama 3.3 70B on Vertex is roughly $0.72/$0.72. Plus Google Cloud egress and Vertex feature fees. Via VerticalAPI BYOK you pay Google Cloud directly with zero token markup.
How do I use Vertex AI via VerticalAPI BYOK?
Create a Google Cloud service account with aiplatform.user role, download the JSON key, paste it into VerticalAPI (with project ID and region), then point the OpenAI SDK at https://api.verticalapi.com/v1. VerticalAPI handles GCP auth (signed tokens), translates OpenAI chat completions into Vertex generateContent, and preserves multimodal inputs. Billing remains on your Google Cloud invoice.
What is Vertex AI best for compared to alternatives?
Vertex AI wins for Google Cloud enterprises and for 2M-context multimodal workloads: Gemini 2.5 Pro's video/audio/PDF understanding is unique, and Vertex adds IAM, VPC-SC, CMEK and regional residency. Compared to AI Studio (consumer Gemini API) it adds enterprise controls. Compared to AWS Bedrock or Azure OpenAI it leads on multimodal context but lags on third-party model breadth (Claude is recent, OpenAI absent).
Where is Vertex AI hosted / data privacy?
Vertex AI runs in 20+ Google Cloud regions including us-central1, europe-west1/4, asia-northeast1 and sovereign EU regions. Data is not used to train models. VPC Service Controls, customer-managed encryption keys, Access Transparency and EU Data Residency are available. Via VerticalAPI BYOK your GCP project remains the data controller with full Cloud Audit Logs.
Limitations and trade-offs
- Authentication is heavier than API keys — requires Google Cloud project, IAM, service accounts.
- Model availability per region varies — Gemini Pro is global but Claude on Vertex is US/EU only.
- Vertex egress and feature fees stack on top of token pricing — total cost can exceed list.
- Quotas (QPM, TPM) are per region and per project and often need explicit increase requests.
- Some open-weight models on Model Garden require manual deployment and pay-per-hour endpoint hosting.
Where Vertex AI is heading
- Gemini 3 launching on Vertex with deeper agentic capabilities and tool use.
- Wider third-party model availability (rumored Llama 4, OpenAI partnerships via partner gateways).
- Expanded Agent Builder and Vertex AI Search for grounded RAG.
- More sovereign EU and APAC region launches for regulated industries.
Related questions
ChatGPT, Perplexity and Gemini usually suggest these next.
- Vertex AI vs AI Studio — when to use each?
- How do I run Claude Sonnet 4.5 on Vertex AI?
- Vertex AI vs AWS Bedrock for multi-model enterprise gateway?
- Best Vertex AI region for low-latency in Europe?
- How to use Vertex AI grounding with Google Search for RAG?
All supported LLM providers
Same endpoint, same SDK — just change the model and the BYOK header.
Ship on Google Vertex AI in 60 seconds
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