Last refreshed 2026-07-26. Next refresh: weekly.
Why use Claude Opus 4.5 on Vercel AI Gateway?
Vercel AI Gateway offers Claude Opus 4.5 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 4.5 across 6 providers to find the best fit for your use caseInput / 1M
$5.00
Output / 1M
$25.00
Cache
read $0.50
Batch
Not sourced
Setup recipe
Python + curlInstall
pip install openaiAuth
export AI_GATEWAY_API_KEY=...Call
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["AI_GATEWAY_API_KEY"],Model ID
anthropic/claude-opus-4.5Request 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-4.5",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Gotchas
- Use provider model ID "anthropic/claude-opus-4.5", not the LLMReference slug "claude-opus-4-5".
- 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 4.5 Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| Microsoft Foundry | $5.00 | $25.00 |
| Anthropic | $5.00 | $25.00 |
| GCP Vertex AI | $5.00 | $25.00 |
| AWS Bedrock | $18.00 | $90.00 |
| OpenRouter | $5.00 | $25.00 |
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $5.00 |
| Output tokens | $25.00 |
| Query | $10.00 |
Capabilities
VisionMultimodalReasoningJSON / Tool useStructured OutputsCode Execution
About Claude Opus 4.5
Claude Opus 4.5 is Anthropic's Claude 4.5 model with multimodal text and image input and an optional reasoning mode. It offers a 200K-token context window and scores 80.7 on MMMU.
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Model Specs
Released2025-11-01
Context200k
ArchitectureDecoder Only
Knowledge cutoff2025-12