Analysis Summary
Claude Opus 4.1 is Anthropic's latest Opus-tier model, combining an intelligence index of 33.7 with an agentic index of 52.9 and a tau2 score of 0.714, placing it among the stronger agentic performers in the benchmarked field. Vision support, tool use, function calling, and file input make it one of the most capable multimodal options available. The 200K context window handles large codebases and long documents comfortably.
For businesses, Opus 4.1 suits autonomous coding agents, complex multi-step workflows, long-document analysis, and client-facing content where accuracy and reliability are critical. The ifbench score of 0.554 and lcr of 0.663 confirm strong instruction following and long-context reasoning. The GPQA of 0.809 and MMLU-Pro of 0.880 reflect broad knowledge depth.
The main trade-off is cost: at $15 input and $75 output per million tokens, it is among the most expensive models available. Reserve it for high-value tasks where quality justifies the premium, and pair with cheaper models for routine volume work.
Assessed July 10, 2026
Editorial notes
Claude Opus 4.1 from Anthropic delivers strong reasoning, a 52.9 agentic index, vision support, and best-in-class instruction following, with a 200K context window for complex document and coding workflows.
Rankings consider pricing, capabilities, benchmarks, and real-world applicability and are refreshed as new models launch. Feedback?
DFO Verdict
Claude Opus 4.1 from Anthropic delivers strong reasoning, a 52.9 agentic index, vision support, and best-in-class instruction following, with a 200K context window for complex document and coding workflows.
Benchmark scores
Magenta = intelligence Ā· Ink = technical/agentic Ā· Cyan = content & long-context Ā· Grey = community benchmarks. Data: Artificial Analysis, Hugging Face.
33.7 Intelligence IndexĀ·52.9 Agentic IndexĀ·80.3 Math Index
How Anthropic: Claude Opus 4.1 compares
Anthropic: Claude Opus 4.1 ranks #64 of 393 AI models we track for overall intelligence, #72 of 300 for agentic tasks. Its 200K-token context window is larger than 63% of the models we list. At $15.00 per million input tokens it is cheaper than 2% of comparable models.
Dark bar = input Ā· light bar = output, scaled to the priciest peer.
1M tokens ā 8 full-length novels or ~2,500 pages of business documents in a single request.
Strongest on content. The pulled-in value corner is the trade-off, and if the shape matters more than the price, this is your model.
Compare shapes side-by-side āPricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $15.00 | $0.015000 |
| Output | $75.00 | $0.075000 |
What would Anthropic: Claude Opus 4.1 cost your business?
Pick the job that looks most like yours, then fine-tune with the sliders. Estimates update live.
A website chatbot handling around 100 customer conversations a day, a few short messages each.
Full calculator with 612 models ā Price Calculator
These numbers get smaller with the right architecture.
We route routine calls to cheap models and save Anthropic: Claude Opus 4.1 for the hard ones. Most clients cut their estimate by 60-80%.
Talk to our teamAbout Anthropic: Claude Opus 4.1
Claude Opus 4.1 is an updated version of Anthropicās flagship model, offering improved performance in coding, reasoning, and agentic tasks. It achieves 74.5% on SWE-bench Verified and shows notable gains..
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Frequently asked questions about Anthropic: Claude Opus 4.1
How much does Anthropic: Claude Opus 4.1 cost?
Anthropic: Claude Opus 4.1 costs $15.00 per million input tokens and $75.00 per million output tokens.
What is the context window of Anthropic: Claude Opus 4.1?
Anthropic: Claude Opus 4.1 has a context window of 200,000 tokens (200K).
What can Anthropic: Claude Opus 4.1 do?
Anthropic: Claude Opus 4.1 supports image/vision input, tool use, and function calling.
Who created Anthropic: Claude Opus 4.1?
Anthropic: Claude Opus 4.1 is developed by Anthropic and was released on August 5, 2025.
Data sourced from the OpenRouter API, Artificial Analysis, the Hugging Face Open LLM Leaderboard and our own internal testing. Scores are editorially curated by our team.
Last updated: July 19, 2026 8:38 pm