Speed
Output tokens / second
Claude Opus 4.5 overview
Claude Opus 4.5 by Anthropic
Anthropic positions Claude Opus 4.5 as its best model for coding, agents and computer use: state-of-the-art on tests of real-world software engineering, and leading across seven of eight programming languages. It handles ambiguity and reasons about tradeoffs without hand-holding, is effective at managing a team of subagents, and reaches similar or better outcomes on dramatically fewer tokens than its predecessors, at medium effort it matches Sonnet 4.5 while using 76% fewer output tokens. Served with a 200K context window.
Claude Opus 4.5 specs
- Model ID
anthropic/claude-opus-4.5- Developer
- Anthropic
- Context window
- 200,000 tokens
- Max output
- 64,000 tokens
- Input
- Text, Image
- Output
- Text
- API
- OpenAI-compatible, base URL
https://api.aimlapi.com/v1
Claude 4.5 Opus API Overview
Claude 4.5 Opus sets a new standard in AI performance, focusing on intelligence, efficiency, and practical utility. This model excels in complex tasks like coding, agentic operations, and deep research, while prioritizing robust safety and alignment.
Technical Specifications
- Context Window: Supports up to 200K tokens, enabling handling of extensive inputs for long-form analysis and multi-step processes.
- Multimodality: It can process various input types, including text, code, images, and documents. It excels at visual reasoning tasks like understanding charts and diagrams and extracting structured data from screenshots.
- Output: The model generates text output.
Performance Benchmarks
Claude Opus 4.5 demonstrates leadership in key evaluations, outperforming predecessors and peers in efficiency and capability.
SWE-bench Verified (Software Engineering): Achieves state-of-the-art scores among frontier models, surpassing previous benchmarks with 4.3 percentage points improvement over Sonnet 4.5 at high effort.
Output Quality & Reasoning Performance
Users report markedly more natural, contextually rich responses with internal stepwise reflection improving answer correctness and detail. The model shows superior handling of complex instructions with balanced conversational tone and precision.
Key Features
- Advanced Reasoning and Ambiguity Handling: Independently navigates tradeoffs, fixes multi-system bugs, and resolves complex issues without explicit guidance.
- Creative Problem-Solving: Employs novel strategies in agentic scenarios, such as policy-compliant workarounds in restricted tasks.
- Token-Efficient Processing: Matches or exceeds prior model performance using significantly fewer tokens, optimizing for cost and speed.
- Robust Alignment and Safety: Features the lowest rates of concerning behaviors, including resistance to misuse and prompt injections, as validated by external audits.
- Agentic Toolset: Supports context compaction, memory retention, and multi-agent coordination for extended, collaborative workflows.
Use Cases
- Software Engineering and Coding: Ideal for building detailed plans, debugging code, researching repositories, and executing multi-step implementations.
- Agentic and Automation Tasks: Handles real-world interactions, such as acting as a virtual assistant for customer support or managing multi-turn processes across systems.
- Deep Research and Analysis: Excels in synthesizing information from slides, spreadsheets, and web sources, supporting in-depth investigations and report generation.
- Professional Evaluations: Simulates human-level performance in assessments like engineering interviews, aiding recruitment and training.
- Collaborative Workflows: Coordinates subagents for complex projects, enabling scalable AI teams in enterprise settings.
- Everyday Productivity: Assists with tasks involving desktop apps, browsers, and documents, streamlining workflows in business and creative fields.
Use cases
- Software Engineering and Coding: Ideal for building detailed plans, debugging code, researching repositories, and executing multi-step implementations.
- Agentic and Automation Tasks: Handles real-world interactions, such as acting as a virtual assistant for customer support or managing multi-turn processes across systems.
- Deep Research and Analysis: Excels in synthesizing information from slides, spreadsheets, and web sources, supporting in-depth investigations and report generation.
- Professional Evaluations: Simulates human-level performance in assessments like engineering interviews, aiding recruitment and training.
- Collaborative Workflows: Coordinates subagents for complex projects, enabling scalable AI teams in enterprise settings.
- Everyday Productivity: Assists with tasks involving desktop apps, browsers, and documents, streamlining workflows in business and creative fields.
Capabilities
- Function calling
- Streaming
- Structured outputs
- Reasoning
- Web search
Claude Opus 4.5 benchmarks by 
Artificial Analysis
See how Claude Opus 4.5 compares in generation speed and latency. Data retrieved Nov 4, 2026.
Benchmark results
Compare 15 models available on AI/ML API across 5 independent benchmarks.
Humanity's Last Exam
Expert-written questions across academic subjects.
GPQA Diamond
Graduate-level science questions written to resist web search.
AA-LCR
Reasoning across long documents of about 100k tokens.
IFBench
Following precise instructions about the shape of the answer.
τ²-Bench Telecom
Customer support agent tasks with tool calls.
Claude Opus 4.5 API pricing
| Usage | Price | Unit |
|---|---|---|
| Input | $5 | 1M tokens |
| Output | $25 | 1M tokens |
| Cached input | $0.529 | 1M tokens |
Prices from the AI/ML API price list, checked on Nov 4, 2026.
Claude Opus 4.5 vs other models: token prices
AI/ML API input and output rates for 5 models, per million tokens.
| Model | Input | Output |
|---|---|---|
 Claude Opus 4.5 | $5 | $25 |
| Claude Haiku 5.5 | $0.1 | $0.5 |
| Claude Sonnet 5.5 | $2 | $10 |
| Claude Opus 5.5 | $4 | $20 |
| Claude Fable 5.1 | $10 | $50 |
How to use the Claude Opus 4.5 API
View docs
Build with your agent
Give your agent the model details, code and documentation.
Paste it into your coding agent to build the integration.
1Get your API key
Create API keyexport AIMLAPI_KEY="8f2b4c7d9a1e6b3f…"2Make your first request
curl 'https://api.aimlapi.com/v1/chat/completions' \
-H "Authorization: Bearer $AIMLAPI_KEY" \
-H 'Content-Type: application/json' \
-d '{
"model": "anthropic/claude-opus-4.5",
"messages": [
{
"role": "user",
"content": "Write a haiku about the ocean."
}
]
}'import os
import requests
headers = {
"Authorization": f"Bearer {os.environ['AIMLAPI_KEY']}",
"Content-Type": "application/json",
}
payload = {
"model": "anthropic/claude-opus-4.5",
"messages": [
{
"role": "user",
"content": "Write a haiku about the ocean."
}
]
}
response = requests.post("https://api.aimlapi.com/v1/chat/completions", headers=headers, json=payload, timeout=120)
response.raise_for_status()
print(response.json())const response = await fetch("https://api.aimlapi.com/v1/chat/completions", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.AIMLAPI_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"model": "anthropic/claude-opus-4.5",
"messages": [
{
"role": "user",
"content": "Write a haiku about the ocean."
}
]
}),
});
if (!response.ok) throw new Error(`HTTP ${response.status}`);
console.log(await response.json());Models similar to Claude Opus 4.5
Related articles
Claude Opus 4.5 FAQ
What is the context window of Claude Opus 4.5?
Claude Opus 4.5 has a 200,000 tokens context window and can return up to 64,000 tokens.
What inputs and outputs does Claude Opus 4.5 support?
Claude Opus 4.5 takes text as input and returns text.
What is the model ID for Claude Opus 4.5?
Use anthropic/claude-opus-4.5 as the model id. Requests go to https://api.aimlapi.com/v1/chat/completions.
How much does Claude Opus 4.5 cost?
Claude Opus 4.5 costs $5 input and $25 output per 1M tokens on AI/ML API, billed as you go with no subscription.
Does Claude Opus 4.5 support streaming?
Yes, Claude Opus 4.5 can stream responses as they are generated.
Who created Claude Opus 4.5?
Claude Opus 4.5 was built by Anthropic.