Roboflow
Anthropic

Anthropic: Claude Opus 4.5

Claude Opus 4.5 Overview

Claude Opus 4.5 is Anthropic’s most advanced large language model in the Claude Opus family, designed for high-end reasoning, coding, and autonomous agent workflows. Released in late 2025, it targets developers and enterprises that need reliable long-context understanding and strong multi-step problem solving in production environments.

The model supports text and code natively, with reported multimodal capabilities for documents and images, and offers an exceptionally large context window of up to roughly 200,000 tokens. Claude Opus 4.5 emphasizes long-horizon task execution, complex code generation and refactoring, and sustained reasoning over large inputs. In the current landscape, it positions itself as a premium, accuracy- and reasoning-focused alternative to faster or cheaper peers, trading cost for depth and contextual fidelity. Typical applications include advanced coding assistants, research analysis, agentic automation, and enterprise knowledge workflows deployed via Anthropic’s API or major cloud platforms.

Claude Opus 4.5 Interactive Demo

Claude Opus 4.5 Details & Performance

Details

Resources

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Vision Tasks

CaptioningChart Question AnsweringClassificationDocument Question AnsweringImage TaggingMulti-Label ClassificationOCRObject DetectionVision LanguageVisual Question Answering

Features

Foundation VisionLLMs with Vision CapabilitiesMultimodal Vision

Usage

Past 30 Days

Performance

Avg. Latency

Arena Rankings

Claude Opus 4.5 Pricing

Claude Opus 4.5 costs $5.00 per 1M input tokens and $25.00 per 1M output tokens.

Input$5.00 / 1M tokens
Output$25.00 / 1M tokens
Cached input$0.500 / 1M tokens

Pricing updated Aug 7, 2026

Alternatives to Claude Opus 4.5

Other models worth comparing for similar use cases.

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Other Anthropic Opus models

Other versions in the same family as Claude Opus 4.5.

AnthropicClaude Opus 5AnthropicClaude Opus 4.8AnthropicClaude Opus 4.7AnthropicClaude Opus 4.6

Deploy Claude Opus 4.5 with an API

Claude Opus 4.5 runs as a hosted REST endpoint through Roboflow Workflows. Pick a task, then hand the prompt to your coding agent or copy the code. Forking the workflow into a free Roboflow workspace replaces the your-workspace and YOUR_API_KEY placeholders with your own.

Connect your agent to Roboflow (once)

Add the Roboflow MCP server

claude mcp add --transport http roboflow https://mcp.roboflow.com/mcp

Run /mcp and authorize Roboflow in your browser when the OAuth flow opens.

Start a new Claude Code session so the MCP loads, then paste the prompt below (it works the same in any agent).

Fork this workflow to your Roboflow workspace to use it.

Integrate the Roboflow "Claude Opus 4.5" workflow into my app.

- Endpoint: POST https://serverless.roboflow.com/<your-workspace>/workflows/playground-claude-4-5-opus-c
- Auth: send my Roboflow API key as `api_key` in the request body, read from the ROBOFLOW_API_KEY env var (never hardcode).
- Body: { "api_key": ..., "inputs": { `image`: { type: "url" | "base64", value }, `model_api_key`: my provider key } }.

With the Roboflow MCP connected, call `workflows_get` on "playground-claude-4-5-opus-c" to read the exact input schema and treat it as the source of truth. A live `workflows_run` for this workflow also needs my Anthropic key (`model_api_key`) passed as a runtime parameter; if you don't have it yet, skip the test run — it will fail with a server error without the provider key, which is expected and not a problem with your code — and rely on the schema. Validate the real run via the REST call once the keys below are set. Without the MCP, use the contract above.

Before running the app, set up these keys so it does not error at runtime:
- `ROBOFLOW_API_KEY` (sent as `api_key`) from https://app.roboflow.com/settings/api
- `ANTHROPIC_API_KEY` (sent as `model_api_key`) from https://console.anthropic.com/settings/keys — my Anthropic key
Create a .gitignore'd .env with these variables, using placeholder values for any I haven't given you. Then pause and tell me directly, in your reply: the full path to the .env file, exactly which keys I need to paste in, and the link to get each one. Wait for me to confirm I've added them before you run anything. Do not run the app until I confirm.

Then add the integration to my codebase: match my project's language, framework, and conventions; read every key from environment variables (never hardcode); add basic error handling; and include a small runnable example. If you can't tell what language my project uses, ask me.
Installpip install inference-sdk

Fork this workflow to your Roboflow workspace to use it.

# 1. Import the library
from inference_sdk import InferenceHTTPClient

# 2. Connect to your workflow
client = InferenceHTTPClient(
  api_url="https://serverless.roboflow.com",
  api_key="YOUR_API_KEY"
)

# 3. Run your workflow on an image
result = client.run_workflow(
  workspace_name="your-workspace",
  workflow_id="playground-claude-4-5-opus-c",
  images={
    "image": "YOUR_IMAGE.jpg"  # Path to your image file
  },
  parameters={
    "model_api_key": "YOUR_ANTHROPIC_API_KEY"
  },
  use_cache=True  # cache workflow definition for 15 minutes
)

# 4. Get your results
print(result)

Fork this workflow to your Roboflow workspace to use it.

const response = await fetch('https://serverless.roboflow.com/your-workspace/workflows/playground-claude-4-5-opus-c', {
  method: 'POST',
  headers: {
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    api_key: 'YOUR_API_KEY',
    inputs: {
      "image": {"type": "url", "value": "IMAGE_URL"},
      "model_api_key": "YOUR_ANTHROPIC_API_KEY"
    }
  })
});

const result = await response.json();
console.log(result);

Fork this workflow to your Roboflow workspace to use it.

curl --location 'https://serverless.roboflow.com/your-workspace/workflows/playground-claude-4-5-opus-c' \
--header 'Content-Type: application/json' \
--data '{
  "api_key": "YOUR_API_KEY",
  "inputs": {
    "image": {"type": "url", "value": "IMAGE_URL"},
    "model_api_key": "YOUR_ANTHROPIC_API_KEY"
  }
}'

Claude Opus 4.5 License

Proprietary

License terms and commercial-use guidance for Claude Opus 4.5.

This model is proprietary. The author retains all rights, and use of the model is governed by their specific terms of service or license agreement.

Commercial use depends on the terms set by the model author. Most proprietary commercial models require a paid subscription, API key, or per-call billing. Check the provider’s pricing and terms-of-service for details.

License information is provided as a guide and is not legal advice.