Last refreshed 2026-07-26. Next refresh: weekly.
Why use Claude Opus 5 on Vercel AI Gateway?
Vercel AI Gateway offers Claude Opus 5 with pay-as-you-go pricing at $5.00/1M input tokens. Vercel AI Gateway is a unified AI proxy providing a single OpenAI-compatible API endpoint to 275+ models from 25+ providers including Anthropic, OpenAI, Google, Meta, Mistral, DeepSeek, xAI, Alibaba, Amazon, ByteDance, Cohere, MiniMax, MoonshotAI, KwaiPilot, Black Forest Labs, Recraft, Voyage AI, NVIDIA, and more.
Compare Claude Opus 5 across 7 providers to find the best fit for your use caseSetup recipe
Python + curlpip install openaiexport AI_GATEWAY_API_KEY=...import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["AI_GATEWAY_API_KEY"],anthropic/claude-opus-5Request example
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["AI_GATEWAY_API_KEY"],
base_url="https://ai-gateway.vercel.sh/v1"
)
response = client.chat.completions.create(
model="anthropic/claude-opus-5",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Gotchas
- Use provider model ID "anthropic/claude-opus-5", not the LLMReference slug "claude-opus-5".
- creator/model-name e.g. kwaipilot/kat-coder-pro-v2
- The examples expect AI_GATEWAY_API_KEY; rename it only if your application config maps the new variable.
Compare Claude Opus 5 Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| Anthropic | $5.00 | $25.00 |
| AWS Bedrock | — | — |
| GCP Vertex AI | $5.00 | $25.00 |
| Microsoft Foundry | — | — |
| OpenRouter | $5.00 | $25.00 |
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $5.00 |
| Output tokens | $25.00 |
| Image input | $1.00 |
Capabilities
About Claude Opus 5
Claude Opus 5 is Anthropic's July 2026 flagship Opus model for complex agentic coding, enterprise work, long-horizon reasoning, computer use, and professional analysis. It accepts text and image input and returns text, with adaptive thinking enabled by default and five request-level effort settings from low through max that control thinking depth and token use rather than visible response length. It also supports tool use, structured outputs, prompt caching, Batch API, a 1M-token context window, and up to 128K synchronous output tokens.