Speed
Output tokens / second
Claude Opus 4.6 overview
Claude Opus 4.6 by Anthropic
With support for massive context windows and scalable agent-based workflows, Claude 4.6 Opus handles tasks beyond standard language models.
Claude Opus 4.6 specs
- Model ID
anthropic/claude-opus-4-6- Developer
- Anthropic
- Context window
- 200,000 tokens
- Max output
- 128,000 tokens
- Input
- Text, Image
- Output
- Text
- API
- OpenAI-compatible, base URL
https://api.aimlapi.com/v1
Claude Opus 4.6 API Overview
Claude Opus 4.6 delivers a step‑change in reliability and intelligent autonomy, combining a million‑token context window (beta), adaptive thinking, and powerful agentic capabilities in one premium model.
What Is Claude 4.6 Opus?
Claude 4.6 Opus is the flagship model in the Claude 4 generation, engineered to handle demanding cognitive workloads that exceed the capabilities of standard large language models. It is optimized for scenarios where precision, consistency, and extended reasoning matter more than speed alone.
Unlike lighter models focused on conversational tasks, Claude 4.6 Opus excels at end-to-end execution: understanding complex inputs, maintaining context over long sessions, and producing structured, high-quality outputs suitable for real-world deployment.
Performance Benchmarks
- Strong long-context reasoning performance across benchmarks that evaluate sustained attention, multi-step logic, and information retrieval over very large inputs.
- High accuracy in complex coding benchmarks, including code generation, refactoring, and debugging tasks involving multi-file and multi-module projects.
- Improved analytical benchmark results in research, legal, and financial scenarios that require structured thinking, consistency, and precise interpretation of data.
- Stable and coherent output quality in extended evaluations, where maintaining context and reasoning quality over long sessions is critical.
Deep Reasoning and Planning
Opus 4.6 is tuned to read the full picture before acting, mapping file structures, dependencies, and patterns so it can plan multi‑step solutions instead of producing shallow, one‑shot answers. It stays with hard problems longer, explores alternatives independently, and commits to a direction once it has enough context, making it suitable for nuanced product, technical, and organizational decisions.
Advanced Coding and Software Engineering
Opus 4.6 delivers production‑ready code with stronger code review, debugging, and large‑codebase navigation than earlier Claude models. It scored at the top of coding evaluations like Terminal‑Bench 2.0 and is designed to autonomously close issues, manage repositories, and coordinate multi‑repo tasks with minimal human hand‑holding.
Agentic Workflows and Tool Use
The model excels at agentic terminal coding, computer use, and sophisticated tool calling, enabling workflows where it operates software, searches, and internal tools on your behalf. Features like agent teams let multiple Claude Code sessions collaborate on complex tasks, while adaptive thinking decides when to invest more reasoning effort versus returning faster answers.
Use cases
Claude Opus 4.6 is documented as suited to coding, enterprise agents, and professional work, including complex coding projects and multi-step development tasks.
It is also suited to financial analysis, where it can synthesize regulatory filings, market reports, and internal data into insights.
The model is documented for research and document-heavy knowledge work, including pulling relevant information from large document sets and creating documents, spreadsheets, and presentations.
It is also suited to agentic workflows and computer use, handling complex multi-step tasks across many tools and visual interfaces with reliability.
Capabilities
- Function calling
- Streaming
- Structured outputs
- Reasoning
- Web search
Claude Opus 4.6 benchmarks by 
Artificial Analysis
See how Claude Opus 4.6 compares in generation speed and latency. Data retrieved Nov 3, 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 4.6 API pricing
| Usage | Price | Unit |
|---|---|---|
| Input | $5 | 1M tokens |
| Output | $25 | 1M tokens |
| Cached input | $0.5 | 1M tokens |
Prices from the AI/ML API price list, checked on Nov 4, 2026.
Claude Opus 4.6 vs other models: token prices
AI/ML API input and output rates for 5 models, per million tokens.
| Model | Input | Output |
|---|---|---|
 Claude Opus 4.6 | $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 4.6 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-4-6",
"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-4-6",
"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-4-6",
"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 4.6
Related articles
Claude Opus 4.6 FAQ
What is the context window of Claude Opus 4.6?
Claude Opus 4.6 has a 200,000 tokens context window and can return up to 128,000 tokens.
What inputs and outputs does Claude Opus 4.6 support?
Claude Opus 4.6 takes text as input and returns text.
What is the model ID for Claude Opus 4.6?
Use anthropic/claude-opus-4-6 as the model id. Requests go to https://api.aimlapi.com/v1/chat/completions.
When was Claude Opus 4.6 released?
Claude Opus 4.6 became available on February 6, 2026.
How much does Claude Opus 4.6 cost?
Claude Opus 4.6 costs $5 input and $25 output per 1M tokens on AI/ML API, billed as you go with no subscription.
Does Claude Opus 4.6 support streaming?
Yes, Claude Opus 4.6 can stream responses as they are generated.
Who created Claude Opus 4.6?
Claude Opus 4.6 was built by Anthropic.