Claude Sonnet 4.6

Name: Claude Sonnet 4.6
Price: 3 USD
Author: Anthropic

Anthropicfrontier

Anthropic's balanced frontier model that approaches Opus 4.6 quality at 60% lower cost. An exceptional coder in its own right with strong reasoning, 1M context (beta), and Anthropic's safety alignment. The recommended default for most Anthropic API users.

Released 2026-01-22Knowledge cutoff: 2025-10

Medium confidence|Updated 55d ago|93% source confidence

Specifications

Context Window

1M tokens

Max Output

64K tokens

Input Price

$3.00 / 1M tokens

Output Price

$15.00 / 1M tokens

Latency Tier

Fast (speed score: 7/10)

Capability Profile

Coding

9.5/10

Structured Output

9.5/10

Instruction Following

9.5/10

Safety & Enterprise

9.5/10

Reasoning

9/10

Long Context

9/10

Factuality

9/10

Tool Use

9/10

Conversational

9/10

Creativity

8.5/10

Multimodal

7/10

Speed

7/10

Cost Efficiency

6.5/10

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 No

Web Search No

Best Use Cases

Production coding assistants and agentic developer tools

Enterprise applications where Opus quality is desired but budget matters

Complex document analysis and structured extraction over long contexts

Multi-turn agentic workflows with tool use and computer use

General-purpose assistant applications requiring high quality and safety

Not Ideal For

The absolute hardest coding problems — Opus 4.6 has a measurable edge

Audio or video processing

Ultra-budget batch workloads where Haiku is sufficient

Tasks requiring the most permissive content policy

Strengths

Coding quality is within ~3-5% of Opus 4.6 on SWE-bench at 40% of the cost

Faster inference than Opus while maintaining strong quality

Excellent structured output compliance and JSON generation

Strong extended thinking mode for reasoning-heavy tasks

1M context beta with good needle-in-haystack performance

Weaknesses

Gap vs Opus is visible on the hardest SWE-bench problems and complex refactors

No audio or video support

More expensive than GPT-5.4-mini for slightly better quality

Safety alignment can feel restrictive for edge-case creative tasks

Edge Cases & Notes

Extended thinking mode closes much of the gap with Opus on reasoning tasks

Prompt caching provides significant cost reduction for repeated system prompts

The quality gap vs Opus narrows on well-structured, explicit prompts

Provider Notes

Anthropic's recommended model for most use cases. Available through Anthropic API, Amazon Bedrock, Google Cloud Vertex AI. Prompt caching and batching available for cost optimization.

Benchmarks

MMLU91.5%

HumanEval94.8%

Arena Elo1400

Benchmark Notes

SWE-bench Verified ~62%. HumanEval 94.8%. MMLU-Pro 91.5%. Close to Opus on most benchmarks. LMSYS Arena shows near-indistinguishable human preference vs Opus for many task types.

Research Meta

Last Evaluated

2026-04-01

Source Confidence

93%

Evaluation Method

SWE-bench Verified, LMSYS Arena, MMLU-Pro, comparative testing vs Opus 4.6

Needs Re-evaluation

Sources

Anthropic Claude Sonnet 4.6 model card (Jan 2026)
SWE-bench Verified leaderboard
LMSYS Chatbot Arena
Artificial Analysis

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