Claude on Vertex AI or a separate gateway: 2026 comparison

In 2026 Claude is available through at least four channels: directly from Anthropic, through AWS Bedrock, through Google Vertex AI, and through independent gateways such as codexkey. For teams already on Google Cloud, Vertex AI is the obvious procurement path. If you are not on GCP, or you want to pay in rubles, euros or crypto, a gateway built around Claude is usually faster to adopt and cheaper to run.

This article puts Google Vertex AI and codexkey side by side for Claude workloads in 2026. We'll look at what each platform gives you, where the price lands, what the SDK swap looks like, and which team profile fits which option.

What Vertex AI gives you

Google Vertex AI is GCP's unified ML platform. Claude models (the Sonnet, Opus and Haiku families) appear there as Model Garden publishers, next to Gemini, Llama, Mistral and Google's own models. Vertex's strengths are GCP-native:

• IAM and organization policy. Service accounts, workload identity federation and org-level guardrails apply to Claude calls as well. You don't end up with a second identity system.
• VPC Service Controls. You can put Vertex inside a VPC SC perimeter, and Claude traffic never crosses the boundary of your private network. For regulated workloads this one feature often decides procurement.
• Regional residency. Anthropic models on Vertex are served from specific Google regions (US, EU, Asia, depending on the model). You pick the region, and the data stays there.
• Gemini next door. One console, one line on the invoice, one SDK pattern for both Gemini and Claude. Handy for A/B tests of models and for fallback chains across vendors.
• A purchasing advantage. If you already signed a committed-use agreement with GCP, Claude spend on Vertex lands in the same contract, on the same invoice, with the same tax handling.

Now the tradeoffs. Vertex has a large surface: before the first API call you need a GCP project, a billing account, IAM bindings and a region. The SDK is the google-cloud-aiplatform / vertexai package (or its REST equivalent), and it is not OpenAI-compatible out of the box. Latency depends on how the region you pick sits relative to your users. EU and Asia regions exist, but coverage is less dense than Anthropic's own edge.

What codexkey gives you

codexkey is a gateway built around Claude, not a hyperscaler ML platform. The scope is deliberately narrow:

• An OpenAI-compatible endpoint. One base URL, https://api.codexkey.online/v1, understands the OpenAI Chat Completions and Messages formats. Any library that works with OpenAI will work with codexkey after you change two strings.
• EU and Russia points of presence. Inference is served from EU and RU edges. That matters to users in those regions and to teams that can't legally route through US-only infrastructure.
• Several ways to pay. Card (Visa, Mastercard, Mir, the Russian national card system), SBP (the Russian Faster Payments System), bank transfer, and the main crypto networks (USDT TRC20/ERC20, BTC, ETH). No GCP billing account, no committed spend, no W-9.
• Pay-as-you-go. You top up a balance and spend it down per request. There are no monthly minimums and no seat licenses.
• One-line setup. Create a key, set OPENAI_API_KEY and OPENAI_BASE_URL, and you are working.

There is a tradeoff here too: codexkey does not replace GCP. No IAM, no VPC SC, no Gemini alongside. If your compliance posture needs a perimeter that includes the model endpoint, take Vertex (or Bedrock, or Anthropic direct over a private link).

Pricing comparison

On Claude model usage itself, Vertex and codexkey are close. Anthropic's published per-token rates set the floor, and both platforms add a margin. In practice:

• Vertex charges Anthropic's list rate for input and output tokens, invoiced in USD to your GCP account. Sustained-use and committed-use discounts can apply if you negotiate a GCP CUD that includes Vertex spend.
• codexkey charges a small markup over Anthropic's list rates, with no minimum and no contract. The markup is transparent, and you can see it per model on the pricing page.

If you spend $500-$5,000 a month on Claude, the all-in cost differs by a few percent. A team spending $50,000+ a month with a serious GCP procurement relationship will usually find Vertex with a CUD cheaper. At $0-$500 a month codexkey is cheaper: there's no contract overhead, no GCP support floor, and no minimum spend.

For a deeper look at Anthropic's underlying rates and how gateways build their prices on top, see the Claude API pricing guide for 2026.

Feature parity

Both platforms offer the same core capabilities: tool use, vision, long context, prompt caching and streaming. Vertex carries Anthropic's full Claude lineup, including Haiku. The codexkey catalog has Haiku too: claude-haiku-5.5 and claude-haiku-4.5, with prices on the models page. They run on the Premium channel, not on Cheap. The cheapest model in the catalog, gpt-5.6-luna, is from a different family, so it is not Claude.

Differences:

Latency

Latency depends on three things: the region of the model, the network path, and the time to first token from Anthropic's serving stack. Vertex's EU regions (europe-west1, europe-west4) give EU users a round trip to the API edge under 100ms, and TTFT for Sonnet-class models on short prompts is typically 400-800ms. codexkey's EU PoP is comparable on RTT, and TTFT is similar: in the end both platforms hit weights hosted by Anthropic.

For users in Russia, codexkey's RU PoP is noticeably faster than any Vertex region. Vertex has no Russian region at all, and traffic from Russia either egresses to the EU or fails outright, depending on routing.

Procurement

This is where the two paths diverge most.

Vertex means a GCP procurement event. You need a GCP organization, a billing account in good standing, and usually a finance review for committed-use discounts. For enterprises already on GCP that costs nothing. For a startup that isn't, it's a multi-week onboarding before the first API call.

codexkey means a self-serve top-up. Sign up, pay by card or crypto, get a key, and go. There's no contract, no NDA, and no SOC2 questionnaire required to start. If your team needs SOC2 attestation further down the chain, Anthropic's own SOC2 covers the model layer whichever gateway routes the call.

Code sample: Vertex SDK vs OpenAI SDK

The same Claude call, written for Vertex and for codexkey.

Vertex AI (Python, vertexai SDK):

from anthropic import AnthropicVertex

client = AnthropicVertex(
    region="europe-west1",
    project_id="my-gcp-project",
)

message = client.messages.create(
    model="claude-sonnet-5@20260101",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Summarize this PR."}],
)

print(message.content[0].text)

This needs gcloud auth application-default login or a service account JSON in the environment, plus the google-cloud-aiplatform and anthropic[vertex] packages.

codexkey (Python, OpenAI SDK):

from openai import OpenAI

client = OpenAI(
    base_url="https://api.codexkey.online/v1",
    api_key="cxa-...",
)

response = client.chat.completions.create(
    model="claude-sonnet-5",
    max_tokens=1024,
    messages=[{"role": "user", "content": "Summarize this PR."}],
)

print(response.choices[0].message.content)

No auth dance, no project ID, no region pinning at the SDK level. If you already have OpenAI SDK code, the change is two lines.

When Vertex wins

Pick Vertex AI when:

• You are already on GCP. Your data is in BigQuery or GCS, your services run on GKE or Cloud Run, and your identity is GCP IAM. Adding Claude as one more Vertex model is the easiest route.
• You need Gemini alongside. If your application splits requests between Gemini and Claude by task type or cost, Vertex gives you one SDK, one invoice and one observability stack for both models.
• You need SOC2 inside a GCP perimeter. VPC Service Controls, IAM and audit logs in one place make a story that passes an enterprise security review faster than "we use a third-party gateway."
• You have a GCP committed-use discount. At high volume, a CUD that covers Anthropic spend on Vertex beats the price of any independent gateway.

When codexkey wins

Pick codexkey when:

• You are not on GCP. You're on AWS, Azure, Hetzner, Yandex Cloud, your own hardware, or you work alone. Vertex's onboarding cost eats any saving.
• You need to pay in rubles or crypto. GCP accepts neither rubles nor crypto, and billing options in CIS countries are limited. codexkey accepts card, SBP, bank transfer and crypto.
• You need OpenAI compatibility. Your stack already speaks the OpenAI API: LangChain, LlamaIndex, the OpenAI SDK, a custom router. Pointing it at codexkey means changing the base URL.
• You want one-line setup. A side project, a prototype, a hackathon, a research notebook. A key in 60 seconds and a working request 60 seconds later.
• Your audience is in the EU or Russia. codexkey's EU/RU PoP is closer to your users than Vertex's nearest region, especially in Russia.

Bottom line

Vertex AI and codexkey don't compete for the same procurement event. Vertex is a feature of GCP: if you live in GCP, use it. codexkey is a gateway built around Claude for everyone else: teams without GCP, teams that don't want to onboard GCP, or teams that need payment rails GCP doesn't offer.

There is good news, too: the SDK swap between them is small. Start the prototype on codexkey, since minutes pass before the first call. If you later move to GCP and want to consolidate billing in Vertex, the Anthropic SDK abstraction keeps most of your application code intact: only the client construction changes.

To compare other gateways, the Claude API pricing guide for 2026 covers Anthropic direct, Bedrock, Vertex and independent gateways in one place.