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Claude Opus 4.6

Anthropicfrontier

Anthropic's flagship model and widely regarded as the best coding model in the world. Achieves the highest SWE-bench Verified score of any model. Features a 1M context window (beta), native computer use, and Anthropic's industry-leading safety alignment. The premium choice for complex software engineering and enterprise applications.

Released 2026-01-22Knowledge cutoff: 2025-10
Medium confidence|Updated 58d ago|95% source confidence

Specifications

Context Window

1M tokens

Max Output

64K tokens

Input Price

$5.00 / 1M tokens

Output Price

$25.00 / 1M tokens

Latency Tier

Moderate (speed score: 5.5/10)

Capability Profile

Coding
10/10
Instruction Following
10/10
Safety & Enterprise
10/10
Reasoning
9.5/10
Long Context
9.5/10
Structured Output
9.5/10
Factuality
9.5/10
Tool Use
9.5/10
Conversational
9.5/10
Creativity
9/10
Multimodal
7.5/10
Speed
5.5/10
Cost Efficiency
3.5/10

Feature Support

Vision Yes
Audio In No
Audio Out No
Video No
Image Generation No
Image Editing No
Function Calling Yes
JSON Mode Yes
Structured Output Yes
Streaming Yes
Reasoning Yes
Realtime No
Computer Use Yes
Web Search No

Best Use Cases

Complex software engineering — the best model for codebase-level refactoring, bug fixing, and feature implementation
Enterprise applications requiring the highest safety and alignment standards
Agentic computer use workflows for GUI automation and testing
Long codebase analysis with 1M beta context window
High-stakes document analysis where accuracy is critical
Constitutional AI research and alignment-sensitive applications

Not Ideal For

Budget-constrained or high-volume workloads — 5x the cost of Sonnet
Real-time interactive applications requiring sub-2s latency
Audio or video processing (vision only)
Simple classification tasks where cheaper models suffice

Strengths

Highest SWE-bench Verified score of any model — unmatched at real-world coding
Industry-leading instruction following and format adherence
Best-in-class safety alignment — Constitutional AI training produces predictably safe behavior
Extended thinking mode enables o3-class reasoning when needed
Computer use capability is robust and production-tested
Exceptional at understanding large codebases and producing coherent multi-file changes

Weaknesses

The most expensive frontier model at $5/$25 per million tokens
Slower inference than GPT-5.4 due to Anthropic's safety-first architecture
No audio or video understanding
1M context is still in beta and may have edge-case quality issues at extreme lengths
Can be overly cautious on borderline requests due to strong safety training

Edge Cases & Notes

Extended thinking mode adds reasoning tokens that significantly increase cost but rival o3 on hard problems
1M context beta requires explicit API flag and may have rate limit restrictions
Computer use works best with structured task descriptions rather than vague goals
Safety refusals are rare but firm — harder to work around than GPT-5.4's boundaries

Provider Notes

Available through the Anthropic API, Amazon Bedrock, and Google Cloud Vertex AI. Prompt caching available for significant savings on repeated prefixes. Enterprise tier available with SLA and priority access.

Benchmarks

MMLU93.1%
HumanEval96.2%
Arena Elo1415

Benchmark Notes

SWE-bench Verified 68.4% (highest of any model). HumanEval 96.2%. MMLU-Pro 93.1%. GPQA Diamond ~72%. Top-2 on LMSYS Arena overall, #1 in coding arena.

Research Meta

Last Evaluated

2026-04-01

Source Confidence

95%

Evaluation Method

SWE-bench Verified, LMSYS Arena, MMLU-Pro, GPQA Diamond, internal coding evaluation across 15 languages

Needs Re-evaluation

No

Sources

  • Anthropic Claude Opus 4.6 model card (Jan 2026)
  • SWE-bench Verified leaderboard
  • LMSYS Chatbot Arena
  • Artificial Analysis quality index

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