ReadyIntel TDX

Anthropic: Claude Opus 4

Model IDanthropic/claude-opus-4

Claude Opus 4 is benchmarked as the world’s best coding model, at time of release, bringing sustained performance on complex, long-running tasks and agent workflows. It sets new benchmarks in software engineering, achieving leading results on SWE-bench (72.5%) and Terminal-bench (43.2%). Opus 4 supports extended, agentic workflows, handling thousands of task steps continuously for hours without degradation. Read more at the blog post here

Start building Docs

input

$15.00/M

output

$75.00/M

context

200K

created

May 23, 2025

Supported API shape

input

image · text · file

output

text

tools

Supported

json mode

Not listed

Verification

signature

response ID

attestation

Intel TDX

provider

1 routes

Providers

anthropic

TDX route

input

$15.00/M

output

$75.00/M

context

200K

$ pip install openai

1from openai import OpenAI
2import os
3
4MODEL = "anthropic/claude-opus-4"
5
6client = OpenAI(
7    base_url="https://api.redpill.ai/v1",
8    api_key=os.environ["REDPILL_API_KEY"],
9)
10
11response = client.chat.completions.create(
12    model=MODEL,
13    messages=[{"role": "user", "content": "Run this privately."}],
14)
15
16print(response.id)
17print(response.choices[0].message.content)

$ npm install openai

1import OpenAI from "openai"
2
3const MODEL = "anthropic/claude-opus-4"
4
5const openai = new OpenAI({
6  baseURL: "https://api.redpill.ai/v1",
7  apiKey: process.env.REDPILL_API_KEY,
8})
9
10const response = await openai.chat.completions.create({
11  model: MODEL,
12  messages: [{ role: "user", content: "Run this privately." }],
13})
14
15console.log(response.id)
16console.log(response.choices[0].message.content)

1curl https://api.redpill.ai/v1/chat/completions \
2  -H "Authorization: Bearer $REDPILL_API_KEY" \
3  -H "Content-Type: application/json" \
4  -d '{
5    "model": "anthropic/claude-opus-4",
6    "messages": [
7      { "role": "user", "content": "Run this privately." }
8    ]
9  }'

More models

Other private inference routes.

View catalog

encrypted

Anthropic: Claude Opus 4.7

Opus 4.7 is the next generation of Anthropic's Opus family, built for long-running, asynchronous agents. Building on the coding and agentic strengths of Opus 4.6, it delivers stronger performance on...

context

input

$5.00/M

encrypted

Anthropic: Claude Sonnet 4.6

Sonnet 4.6 is Anthropic's most capable Sonnet-class model yet, with frontier performance across coding, agents, and professional work. It excels at iterative development, complex codebase navigation, end-to-end project management with memory, polished document creation, and confident computer use for web QA and workflow automation.

context

input

$3.00/M

encrypted

Anthropic: Claude Opus 4.6

Opus 4.6 is Anthropic's strongest model for coding and long-running professional tasks. It is built for agents that operate across entire workflows rather than single prompts, making it especially effective for large codebases, complex refactors, and multi-step debugging that unfolds over time.

context

input

$10.00/M

encrypted

Anthropic: Claude Opus 4.5

Claude Opus 4.5 is Anthropic’s frontier reasoning model optimized for complex software engineering, agentic workflows, and long-horizon computer use. It offers strong multimodal capabilities, competitive performance across real-world coding and reasoning benchmarks, and improved robustness to prompt injection. The model is designed to operate efficiently across varied effort levels, enabling developers to trade off speed, depth, and token usage depending on task requirements. It comes with a new parameter to control token efficiency, which can be accessed using the OpenRouter Verbosity parameter with low, medium, or high. Opus 4.5 supports advanced tool use, extended context management, and coordinated multi-agent setups, making it well-suited for autonomous research, debugging, multi-step planning, and spreadsheet/browser manipulation. It delivers substantial gains in structured reasoning, execution reliability, and alignment compared to prior Opus generations, while reducing token overhead and improving performance on long-running tasks.

context

200K

input

$5.00/M