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AClaude Sonnet 4.6 (batch)API

Sonnet 4.6 is Anthropic's most capable Sonnet-class model yet, with frontier performance across coding, agents, and professional work.

1MContext window · tokens
$1.5Input price · per M tokens
$7.5Output price · per M tokens
AnthropicProvider

Prices update automatically — checked daily against provider list prices.

See open-source alternatives → Compare all model prices

Benchmarks & performance

Independent benchmark scores for Claude Sonnet 4.6 (batch), measured by Artificial Analysis. Higher is better. Measurement mode: Non-reasoning, High Effort.

Intelligence index36.8
GPQA79.9%
Humanity's Last Exam13.3%
Long Context Reasoning62.3%
SciCode46.9%
IFBench41.2%
τ²-Bench79.5%
Terminal-Bench Hard46.2%
💰 Blended price$6 / 1M tokens
📈 Value6.1 intelligence points per $
vs. models measured heretop 36%
Scores higher than 64% of the 273 models measured by Artificial Analysis and tracked here.
Models at this level cost $1.72 per 1M tokens (median of 26) — this one costs $3.
Cheaper and better on this index: GPT-5.6 Sol (batch) · GLM 5.3 · GLM 5.3 Flash and 55 more
Benchmark data by Artificial Analysis

About this model

Claude Sonnet 4.6 (batch) is a commercial AI model by Anthropic. The specifications below are tracked automatically: pricing is refreshed daily from public list prices, so the numbers on this page reflect the current cost of using the model through its API.

Frequently asked questions

What is Claude Sonnet 4.6 (batch)?

Claude Sonnet 4.6 (batch) is an AI language model from Anthropic. It is a proprietary model, available through an API. It scores 36.8 on the Artificial Analysis intelligence index.

Is Claude Sonnet 4.6 (batch) free?

Claude Sonnet 4.6 (batch) is not free: it costs $1.5 per million input tokens and $7.5 per million output tokens. Open-weight alternatives can be self-hosted at no per-token cost.

What is Claude Sonnet 4.6 (batch) good at?

Independent benchmarks from Artificial Analysis give it GPQA 79.9%, Humanity's Last Exam 13.3%, Long Context Reasoning 62.3%, SciCode 46.9%, IFBench 41.2%, τ²-Bench 79.5%, Terminal-Bench Hard 46.2%.

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