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Opus 5.5 Review

Opus 5.5 is Anthropic's flagship AI model designed for complex reasoning, coding, and tool use, capable of generating intricate code for 3D worlds and animations.

shipped Sep 26, 2026freemium
Domain rating92Monthly visits2.3M/mo
Opus 5.5 — product screenshot

Why it matters

1Offers 40% less running cost than Opus 5.
2Cache read costs are reduced to $0.20 per million tokens.
3Output tokens are priced at $20 per million.
4Features enhanced safety measures against prompt injection.

About Opus 5.5

Business Model
Usage-Based (Pay Per Use)
Usage Pricing
$4 per token
Headquarters
San Francisco, USA
Funding
Series B
Total Raised
$580 million
Platforms
Web, API
Target Audience
Software developers, data scientists, and enterprises

Pricing Plans

Standard
$4/1M tokens
  • • Input tokens
  • • Cache reads
  • • Output tokens
Fast Mode
$8/1M input tokens, $40/1M output tokens
  • • Up to 2.5x speed

Cost Examples

  • • Cache reads: $0.20/million tokens
  • • Output tokens: $20/million tokens

Leadership

Dario AmodeiCEOLinkedIn

Investors

Sequoia Capital, Coatue Management, Tiger Global Management

Specs

API Available

Yes, public API

overview

What is Opus 5.5?

Opus 5.5 is a large language model developed by Anthropic that enables software developers, data scientists, and enterprises to perform complex reasoning, coding, and tool use. It excels at generating intricate code for 3D worlds and animations, and is designed for tasks requiring advanced problem-solving capabilities.

features

Key Features of Opus 5.5

Opus 5.5 incorporates several features designed to enhance its performance and utility for advanced AI applications. These include cost efficiencies, robust safety protocols, and improved communication capabilities.

  • 40% reduction in running costs compared to Opus 5.
  • Cache read costs set at $0.20 per million tokens.
  • Output tokens priced at $20 per million tokens.
  • Enhanced safety measures specifically against prompt injection attacks.
  • Improved natural communication for more effective collaborative tasks.
  • API access with a 4-tier usage system for varying rate limits (RPM, ITPM, OTPM).

use cases

Who Should Use Opus 5.5?

Opus 5.5 is primarily targeted at professionals and organizations requiring advanced AI capabilities for complex, technical, and data-intensive tasks. Its design supports applications in various specialized fields.

  • Software developers for coding, debugging, and generating intricate code for 3D worlds and animations.
  • Data scientists for knowledge retrieval, reporting, and complex data analysis.
  • Financial analysts for financial modeling and advanced quantitative tasks.
  • Cybersecurity professionals for threat analysis and other security-related tasks.
  • Biology researchers for complex data processing and scientific inquiry.

how to use

How to Use Opus 5.5

Opus 5.5 can be accessed via its web interface or through its API, allowing for integration into custom applications and workflows. Users can begin by signing up on the Anthropic website.

  • 1Visit the Anthropic website and navigate to the Claude Opus 5.5 section.
  • 2Sign up for an account to access the freemium model.
  • 3For API access, refer to the official API documentation at https://platform.claude.com/docs.
  • 4Integrate the API into existing platforms such as Amazon Web Services, Google Cloud, or Microsoft Azure.
  • 5Utilize the model for tasks like code generation, complex reasoning, or data analysis through direct interaction or programmatic calls.

pricing

Opus 5.5 Pricing & Plans

Opus 5.5 operates on a freemium model, offering different pricing tiers for API usage based on token consumption. The pricing structure includes distinct rates for input and output tokens, as well as reduced costs for cache reads.

  • Standard Tier: $4 per million input tokens.
  • Fast Mode Tier: $8 per million input tokens and $40 per million output tokens.
  • Cache Read Costs: $0.20 per million tokens.
  • Output Token Costs (general): $20 per million tokens.

Pros

  • +Excels at complex reasoning and problem-solving.
  • +Generates intricate code for specialized applications like 3D worlds and animations.
  • +Offers significant cost reductions (40% less running cost than Opus 5).
  • +Includes enhanced safety measures, specifically against prompt injection.
  • +Provides improved natural communication for collaborative and interactive tasks.
  • +API available with tiered usage for scalable enterprise deployments.

Cons

  • −Proprietary model, limiting user control and customization compared to open-source alternatives.
  • −Lacks native multimodal input/output capabilities found in some competitors like GPT-4o.
  • −Integration primarily focused on major cloud providers, potentially less seamless with other ecosystems.
  • −API rate limits are tiered and depend on usage history, which might be a barrier for new high-volume users.
  • −Specific pricing for output tokens ($20 per million) may be a consideration for high-volume text generation.

Policies

Pricing Page

View Pricing→

Similar Tools

Opus 5.5 vs Competitors

Opus 5.5 competes with several other advanced AI models, each offering distinct capabilities and pricing structures. Its primary differentiators lie in its focus on complex reasoning, coding, and specific cost efficiencies.

1
OpenAI GPT-4o↗

GPT-4o is a multimodal model that natively processes and generates text, audio, and image inputs, excelling in real-time interactions and complex reasoning.

While Opus 5.5 is strong in complex reasoning and coding, GPT-4o offers a unified multimodal experience, potentially making it more versatile for applications requiring diverse input types beyond just text and code.

2
Google Gemini Advanced↗

Gemini Advanced (now Google AI Pro) is designed for complex reasoning, code generation, and multi-step problem-solving, with deep integration into Google's ecosystem.

Gemini Advanced offers similar high-level reasoning and coding capabilities to Opus 5.5, but its strength lies in its seamless integration with Google Workspace applications and its 'thinking process' for multi-step tasks.

3
Meta Llama 3↗

Llama 3 is an open-source model available in various parameter sizes, offering strong capabilities in reasoning, code generation, and instruction following, with the flexibility for self-hosting and fine-tuning.

Llama 3 provides the significant advantage of being open-source, allowing for greater control and customization compared to the proprietary Opus 5.5. However, deploying and managing Llama 3 may require more technical expertise and infrastructure.

4
Mistral Large↗

Mistral Large excels in complex reasoning, multilingual tasks, and code generation, offering a balance of high performance and competitive pricing.

Mistral Large offers comparable reasoning and coding prowess to Opus 5.5, often at a more competitive price point for API usage, and is known for its strong multilingual capabilities.

5
Mixtral 8x7B↗

Mixtral 8x7B is a high-quality sparse Mixture-of-Experts (SMoE) model with open weights, known for strong performance in mathematical reasoning, code generation, and multilingual tasks with efficient inference.

As an open-source Mixture-of-Experts model, Mixtral 8x7B offers excellent performance for its size and cost, making it a strong free alternative to Opus 5.5, though it might require more effort for deployment and fine-tuning compared to a hosted solution.

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