Claude Opus 4.6 vs Gemini 3 Pro
Compare Claude Opus 4.6 and Gemini 3 Pro side-by-side. See how these vision models stack up in Open Prompt, OCR, Object Detection, Classification, and Image Captioning.
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Gemini 3 Pro is deprecated and can no longer be run. Details and evals are still available on its model page.
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Claude Opus 4.6 vs Gemini 3 Pro Comparison Table
Evals updated July 10, 2026Pricing updated July 16, 2026
| Property | Claude Opus 4.6 | Gemini 3 Pro |
|---|---|---|
| Organization | Anthropic | |
| Category | closed | closed |
| Modality | multimodal | multimodal |
| Release Date | Feb 2026 | Nov 2025 |
| Context Window | 1.0M | 1.0M |
| Parameters | ||
| License | Proprietary | Proprietary |
| Pricing per 1M tokens | ||
| Input $/1M | $5.00 | |
| Output $/1M | $25.00 | |
| Vision Tasks | ||
| Captioning | Demo | |
| Classification | Demo | |
| Object Detection | Demo | |
| OCR | Demo | |
| Vision Language | ||
| Visual Question Answering | Demo | |
| Model Features | ||
| Foundation Vision | ||
| LLMs with Vision Capabilities | ||
| Multimodal Vision | ||
Claude Opus 4.6 vs Gemini 3 Pro: Overview
Claude Opus 4.6 is the flagship large language model from Anthropic, released on 2026-02-05 for advanced reasoning, complex coding, and enterprise agent workflows. It supports text and image inputs via API, offers a 200K-token standard context window with a 1M-token beta option, and enables outputs up to 128K tokens, with adaptive reasoning and context compaction for sustained tasks.
As of 2026-02-17, Anthropic also released Claude Sonnet 4.6, extending the 1M-token context window to a broader tier. Opus remains positioned for maximum depth and benchmark performance, while Sonnet 4.6 brings long-context capability to more cost- and latency-sensitive production use cases.
Gemini 3 Pro is Google DeepMind’s flagship multimodal frontier model, built for high-accuracy reasoning and large-scale context understanding across text, images, audio, video, code, and documents. It delivers major gains over Gemini 2.5 Pro, supported by a 1M-token window and strong performance on Google-reported benchmarks such as GPQA Diamond, MMMU-Pro, and Video-MMMU.
The model excels at structured outputs, tool use, and agentic coding, enabling complex multi-step workflows and analysis of entire books, codebases, or long videos in a single prompt. Positioned as Google’s top production model, it balances advanced reasoning with broad multimodal capabilities, making it well suited for research assistants, automation agents, coding systems, and enterprise-scale document and media analysis.