latentbrief

Model comparison

Claude Sonnet 4.6 vs Gemini 2.5 Pro

Gemini 2.5 Pro supports a wider range of input modalities, including audio and video, while Claude Sonnet 4.6 focuses on text and image interactions at higher operational costs.

Specs

MetricClaude Sonnet 4.6Gemini 2.5 Pro
Context window1M tokens1.0M tokens
Input $/1M tokens$3.00$1.25
Output $/1M tokens$15.00$10.00
ModalitiesText · ImageText · Image · File · Audio · Video
Open weightsNoNo

How they differ

Input modalities

Claude Sonnet 4.6

Claude Sonnet 4.6 supports text and image inputs, focusing on simpler modality coverage.

Gemini 2.5 Pro

Gemini 2.5 Pro handles text, image, file, audio, and video inputs, offering broader multi-modal capabilities.

Cost profile

Claude Sonnet 4.6

Claude Sonnet 4.6 charges $3.0 per 1M input tokens and $15.0 per 1M output tokens, resulting in higher costs for extensive tasks.

Gemini 2.5 Pro

Gemini 2.5 Pro charges $1.25 per 1M input tokens and $10.0 per 1M output tokens, making it more cost-effective overall.

Context handling

Claude Sonnet 4.6

Claude Sonnet 4.6 has a context window of 1,000,000 tokens, suitable for processing long documents or conversations.

Gemini 2.5 Pro

Gemini 2.5 Pro has a slightly larger 1,048,576-token context window, enabling marginally longer sequential reasoning.

Claude Sonnet 4.6 — what sets it apart

  • +Claude Sonnet 4.6 emphasizes high-interpretability output for narrow applications.
  • +It is tailored for tasks focused on text and image inputs but lacks support for other modalities such as video and audio.

Gemini 2.5 Pro — what sets it apart

  • +Gemini 2.5 Pro supports additional input types, including file, audio, and video data, offering versatility across diverse use cases.
  • +Its multi-modal architecture enables applications that require integrated reasoning across varied media formats.

The most consequential difference is Gemini 2.5 Pro's superior multi-modal input support, allowing it to handle diverse data types not supported by Claude Sonnet 4.6.

Analysis synthesized from gpt-4o, llama-4-maverick, phi-4, etc.