Claude Opus 4.6 vs Gemini 3 Flash

Compare Claude Opus 4.6 and Gemini 3 Flash side-by-side. See how these vision models stack up in Open Prompt, OCR, Object Detection, Classification, and Image Captioning.

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AnthropicClaude Opus 4.6
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GoogleGemini 3 Flash
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Models in this comparison

Claude Opus 4.6 vs Gemini 3 Flash: Overview

Claude Opus 4.6

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 Flash

Gemini 3 Flash is a proprietary multimodal large language model developed by Google through Google DeepMind, designed to deliver fast, cost-efficient reasoning across real-time products and developer workflows. Released in December 2025, it is the Flash-tier variant of the Gemini 3 family, balancing low latency with reasoning quality approaching Pro models.

The model supports text, images, audio, and video, with an exceptionally large context window of roughly one million input tokens and outputs up to ~65k tokens. It emphasizes rapid responses for coding, summarization, analysis, and agentic tasks, and exposes configurable “thinking levels” via API to trade speed for deeper reasoning. Today, Gemini 3 Flash positions itself as a high-throughput, production-ready model, serving as the default in the Gemini app and Google Search’s AI Mode, optimized for scalable, interactive AI applications.

Claude Opus 4.6 vs Gemini 3 Flash Comparison Table

PropertyClaude Opus 4.6 Gemini 3 Flash
OrganizationAnthropicGoogle
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateFeb 2026Dec 2025
Context Window1.0M1.0M
Parameters
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$5.00$0.500
Output $/1M$25.00$3.00
Vision Tasks
CaptioningDemoDemo
ClassificationDemoDemo
Object DetectionDemoDemo
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
Model Features
Foundation Vision
LLMs with Vision Capabilities
Multimodal Vision
Vision Evalspass/fail results · 67 prompts
Score key:≥75%40–74%<40%
Visual Understanding
Overall Score
64.18%
74.63%
Avg Response Time23.35s9.85s
Median input tokensincl. image tokens2.2K1.1K
Median output tokens130290
Est. cost / taskon this benchmark$0.014$0.0014
Defect Detection
73.3%(11/15)
73.3%(11/15)
Document Understanding
77.8%(7/9)
88.9%(8/9)
Object Counting
20%(2/10)
30%(3/10)
Object Understanding
71.4%(10/14)
85.7%(12/14)
Spatial Understanding
68.4%(13/19)
84.2%(16/19)
OCR
Overall Score
82.53%
93.01%
Avg Response Time5.05s12.40s
Median input tokensincl. image tokens7361.1K
Median output tokens99160
Est. cost / taskon this benchmark$0.0062$0.0010
Focused Scene OCR
85.9%(85/99)
94.9%(94/99)
Handwritten Math
70%(7/10)
100%(10/10)
License Plate Recognition
90%(27/30)
100%(30/30)
Text Recognition
80%(24/30)
86.7%(26/30)
VQA & Extraction
76.7%(46/60)
88.3%(53/60)

Output tokens (incl. reasoning) and est. cost / task are measured on this benchmark from a single low-temperature run, and shown only for models whose run covered at least 90% of prompts. Methodology