latentbrief

Model comparison

Gemini 2.5 Pro vs Claude Sonnet 4.6

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

MetricGemini 2.5 ProClaude Sonnet 4.6
Context window1.0M tokens1M tokens
Input $/1M tokens$1.25$3.00
Output $/1M tokens$10.00$15.00
ModalitiesText · Image · File · Audio · VideoText · Image
Open weightsNoNo

How they differ

Input modalities

Gemini 2.5 Pro

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

Claude Sonnet 4.6

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

Cost profile

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.

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.

Context handling

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

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

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.

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.

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.