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Google LLC (Vertex AI)@europe-west1

claude-opus-4-6

Claude Opus 4.6 is Anthropic's most powerful model yet and the best coding model in the world.

πŸ‘Vision🧠ReasoningπŸ”§Tool calling⚑CachingπŸ–₯Computer use
Try claude-opus-4-6CompareDocs

Specifications

Context window1M tokens
Max output128K tokens
API typechat
AddedFeb 5, 2026
Model IDvertex/claude-opus-4-6@europe-west1
Data retentionNo
Used for trainingNo
Provider locationπŸ‡ΊπŸ‡Έ US / πŸ‡ͺπŸ‡Ί EU
Privacy policyVertex AI Data Governance β†’

Benchmarks

Released 2025-12
SWE-Bench Verifiedcoding
74.5%

Resolving real GitHub issues from 12 popular Python repositories.

GPQA Diamondreasoning
81.2%

Graduate-level physics, chemistry & biology questions designed to resist Googling.

MMLU Proknowledge
87.8%

Massive Multitask Language Understanding across 57 academic subjects.

Scores are sourced from official model cards, Artificial Analysis, and public leaderboards. Benchmarks measure specific skills and do not capture every aspect of model quality β€” always test on your own workload.

Pricing

Input / 1M
$5.50
Output / 1M
$27.50
Cache write / 1M
$6.88
Cache read / 1M
$0.55
Estimated cost
100K input + 10K output$0.82
1M input + 100K output$8.25
10M input + 1M output$82.50

Requesty charges exactly what the upstream provider charges β€” no markup, no per-request fees. Prompt caching and smart routing can reduce effective cost by 30-80%.

Quickstart

Drop-in compatible with the OpenAI SDK. Change the base URL, swap in your Requesty API key, and set the model to vertex/claude-opus-4-6@europe-west1.

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from openai import OpenAI

client = OpenAI(
    api_key="YOUR_REQUESTY_API_KEY",
    base_url="https://router.requesty.ai/v1",
)

response = client.chat.completions.create(
    model="vertex/claude-opus-4-6@europe-west1",
    messages=[
        {"role": "user", "content": "Explain quantum computing in one paragraph."},
    ],
)

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

Other Google LLC (Vertex AI) models

kimi-k2
262K ctx$0.60/1M
SWE-Bench 66%
deepseek-v3.2
164K ctx$0.56/1M
gemini-3.1-flash-lite-preview
1.0M ctx$0.25/1M
gemini-3.1-flash-image-preview
131K ctx$0.50/1M
gemini-3-pro-preview
1.0M ctx$2.00/1M
gemini-3.1-pro-preview
1.0M ctx$2.00/1M

Frequently asked questions

How much does claude-opus-4-6 cost?
claude-opus-4-6 is priced at $5.50 per million input tokens and $27.50 per million output tokens when accessed via Requesty. Prompt caching is supported, which can cut effective input cost by up to 90% on repeated context. Requesty charges exactly what the upstream provider charges β€” we don't add markup.
What is the context window of claude-opus-4-6?
claude-opus-4-6 has a context window of 1M tokens, with a maximum output of 128K tokens per response. That's roughly 1,333 words of input you can fit in a single prompt.
How does claude-opus-4-6 perform on benchmarks?
claude-opus-4-6 scores 94.1% on HumanEval, 93.2% on MATH, 87.8% on MMLU Pro. See the full benchmark chart above for results across MMLU Pro, GPQA Diamond, SWE-Bench Verified, HumanEval, MATH, AIME, MMMU, and LiveBench.
What can claude-opus-4-6 do?
claude-opus-4-6 supports vision input, tool calling, extended reasoning, prompt caching, computer use. You can call it through any OpenAI-compatible client by pointing base_url to Requesty.
How do I use claude-opus-4-6 with the OpenAI SDK?
Install the OpenAI SDK, set base_url to "https://router.requesty.ai/v1", set your API key to your Requesty key, and set the model to "vertex/claude-opus-4-6@europe-west1". The Quickstart above shows Python, JavaScript and cURL snippets.
What region is this deployment?
This variant of claude-opus-4-6 is deployed in europe-west1. Region-specific endpoints matter for data residency, latency to your users, and compliance requirements (GDPR, HIPAA). Other regions for the same model may be listed on the Google LLC (Vertex AI) provider page.

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