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Itay Pahima

Senior Developer & Co-founder of Collabria

Claude Opus 4.6: Benchmarks, Pricing & What's New

Anthropic's latest flagship model brings a 1M token context window, improved agentic capabilities, and new coding benchmarks. Here's everything you need to know.

Claude Opus 4.6 at a Glance

Context Window

1M tokens

Input Price

$5.00 / 1M tokens

Output Price

$25.00 / 1M tokens

Overall Score

9.5 / 10

Released February 5, 2026, Claude Opus 4.6 takes the top spot in our overall rankings with a 9.5/10 score, surpassing GPT-5.2 (9.4/10). It leads in coding (9.8), instruction following (9.9), and creative writing (9.5).

Data verified: February 6, 2026

What's New in Claude Opus 4.6

1M Token Context Window

A 5x increase over Opus 4.5's 200K context. Process entire codebases, lengthy legal documents, or multi-document research in a single request. Currently in beta.

Multi-Agent Workflows

Native support for orchestrating teams of AI agents. Opus 4.6 can delegate sub-tasks, coordinate between agents, and synthesize results from parallel workflows.

Enhanced Coding (9.8/10)

The highest coding score we've measured. Excels at large codebase analysis, complex debugging, multi-file refactoring, and understanding architectural patterns across projects.

Adaptive Thinking

Improved extended thinking capabilities that adapt reasoning depth to task complexity. Simple queries get fast responses while complex problems receive deep analysis.

Benchmark Comparison

How does Claude Opus 4.6 stack up against the competition? Here's a head-to-head comparison with GPT-5.2, Claude Opus 4.5, and Gemini 3 Pro.

CapabilityClaude Opus 4.6GPT-5.2Claude Opus 4.5Gemini 3 Pro
coding9.8/109.5/109.7/109/10
reasoning9.6/109.8/109.5/109.3/10
creativity9.5/109/109.5/108.8/10
factual Accuracy9.3/109.2/109/109.5/10
instruction Following9.9/109.5/109.8/109.2/10
Overall Score9.5/109.4/109.3/109.2/10
Context Window1,000K256K200K2,000K

Pricing Analysis

Claude Opus 4.6 matches the pricing of Opus 4.5 at $5.00/$25.00 per 1M tokens for input/output. This positions it as a premium model, but with significantly better performance per dollar than its predecessor.

ModelInput (1M tokens)Output (1M tokens)Score / $
Claude Opus 4.6$5.00$25.001.9
GPT-5.2$2.50$10.003.8
Claude Opus 4.5$3.00$15.003.1
Gemini 3 Pro$1.25$5.007.4

Score / $ = Overall score divided by input price per 1M tokens. Higher is better. Prices as of February 6, 2026.

Should You Upgrade from Opus 4.5?

If you're currently using Claude Opus 4.5, here's what the upgrade to 4.6 gets you:

5x larger context window (200K → 1M tokens)

Process entire codebases and multi-document research in one request

Coding score improvement (9.7 → 9.8)

Better at complex debugging and multi-file refactoring

Multi-agent orchestration

Native support for agent teams and parallel workflows

Instruction following improvement (9.8 → 9.9)

More reliable adherence to complex multi-step instructions

Same pricing as Opus 4.5

$5.00/$25.00 per 1M tokens — more performance for the same cost

Bottom line: If you're on Opus 4.5, the upgrade is a no-brainer — you get better performance at the same price. The main consideration is the slightly slower response times (65 vs 70 tokens/sec), which may matter for latency-sensitive applications.

Test Claude Opus 4.6 yourself

Want more detailed comparisons with scoring and benchmarks?

Best Use Cases for Claude Opus 4.6

Large Codebase Analysis

With 1M tokens of context, analyze entire repositories. Ideal for code review, security audits, and architectural analysis across hundreds of files.

Multi-Agent Workflows

Build AI systems where Opus 4.6 orchestrates multiple sub-agents for complex tasks like automated testing, deployment pipelines, or research synthesis.

Complex Debugging

Trace bugs across large codebases, understand intricate interactions between components, and propose fixes that account for system-wide implications.

Long-Running Agentic Tasks

Extended task execution with improved reliability. Opus 4.6 maintains context and coherence across long-running autonomous workflows.

Frequently Asked Questions

Is Claude Opus 4.6 better than GPT-5.2?

In our benchmarks, Claude Opus 4.6 scores 9.5/10 overall vs GPT-5.2's 9.4/10. Opus 4.6 leads in coding (9.8 vs 9.5), instruction following (9.9 vs 9.5), and creativity (9.5 vs 9.0). GPT-5.2 still leads in reasoning (9.8 vs 9.6). See full comparison →

How much does Claude Opus 4.6 cost?

Claude Opus 4.6 costs $5.00 per million input tokens and $25.00 per million output tokens. This is the same pricing as Opus 4.5 and is 2x more expensive than GPT-5.2 for input tokens ($2.50) but 2.5x more for output tokens ($10.00).

Can Claude Opus 4.6 really handle 1 million tokens?

Yes, though the 1M token context window is currently in beta. Anthropic has confirmed that all Opus 4.6 users have access, but performance at the extremes of the context window may vary compared to shorter contexts.

Should I switch from GPT-5.2 to Claude Opus 4.6?

It depends on your use case. Switch if you need: superior coding capabilities, 1M token context, multi-agent workflows, or better instruction following. Stay with GPT-5.2 if you need: the highest reasoning scores, lower pricing ($2.50 vs $5.00 input), or faster responses.

When was Claude Opus 4.6 released?

Claude Opus 4.6 was released on February 5, 2026. It is available via the Anthropic API and Claude.ai.

Conclusion

Claude Opus 4.6 is a significant step forward for Anthropic and takes the top spot in our overall LLM rankings. The combination of a 1M token context window, best-in-class coding capabilities, and multi-agent support makes it the go-to model for developers building complex AI-powered applications.

For most coding and agentic use cases, Opus 4.6 is now the best choice. For budget-sensitive applications or tasks requiring the highest reasoning scores, GPT-5.2 remains a strong alternative at lower pricing.

Compare Claude Opus 4.6 Side-by-Side

Test Opus 4.6 against GPT-5.2, Gemini 3, and more with your own prompts.

IP
Itay Pahima

Senior Developer & Co-founder of Collabria

Building tools to help developers make data-driven decisions about AI models. Passionate about LLM evaluation, prompt engineering, and developer experience.

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