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Claude Opus 4.8 vs Gemini 2.5 Flash

Compare Claude Opus 4.8 and Gemini 2.5 Flash side-by-side. See how these vision models stack up in Image Captioning, Classification, OCR, Object Detection, and Open Prompt.

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AnthropicClaude Opus 4.8
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GoogleGemini 2.5 Flash
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Claude Opus 4.8 vs Gemini 2.5 Flash: Overview

Claude Opus 4.8

Claude Opus 4.8 is Anthropic's most capable generally available large language model, released on May 28, 2026 as an incremental upgrade to Claude Opus 4.7. The model accepts text and image inputs and produces text outputs, with a 1 million token context window on the Claude API, Amazon Bedrock, and Google Cloud Vertex AI (200k tokens on Microsoft Foundry) and up to 128k max output tokens. It uses adaptive thinking and supports adjustable effort tiers — high by default, with extra and max tiers available for more demanding tasks. A fast mode operates at approximately 2.5x standard speed. The model is described by Anthropic as a hybrid reasoning model designed for advanced coding, agentic workflows, long-context reasoning, and professional knowledge work.

Key behavioral improvements over Opus 4.7 include substantially reduced rates of unreported code flaws, improved honesty in self-assessment, and better tool-calling reliability. On Anthropic's Super-Agent benchmark, Opus 4.8 completes every case end-to-end, and it scores 84% on Online-Mind2Web for computer-use and browser-agent tasks. It achieves 88.6% on SWE-bench Verified and 69.2% on SWE-bench Pro. Alongside the model, Anthropic launched Dynamic Workflows in Claude Code (research preview), which enables Claude to orchestrate hundreds of parallel subagents for codebase-scale tasks such as large migrations. The Messages API was also updated to accept mid-task system messages without breaking prompt caching, improving support for long-running agentic pipelines.

Gemini 2.5 Flash

Gemini 2.5 Flash, released on June 17, 2025, is Google DeepMind’s production-ready, efficiency-focused model in the Gemini 2.5 family. It is multimodal, accepting text, images, video, and audio as inputs, with text as the primary output format. The model supports 1 million input tokens and up to 65K output tokens, enabling it to process very large contexts such as books, long video transcripts, or extensive datasets. Its training knowledge extends to January 2025.

Designed as a price-performance leader, Gemini 2.5 Flash balances speed and reasoning power, making it suitable for everyday enterprise and developer use cases without the higher latency and cost of Pro models. It supports advanced workflows like function calling, code execution, search grounding, URL context ingestion, and structured outputs. While efficient and scalable, output length is still limited compared to its input capacity, and multimodal outputs (e.g. image or audio generation) remain restricted to specialized or preview variants.

Claude Opus 4.8 vs Gemini 2.5 Flash Comparison Table

PropertyClaude Opus 4.8Gemini 2.5 Flash
OrganizationAnthropicGoogle
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateMay 2026Jul 2025
Context Window1.0M1.0M
Parameters
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$5.00$0.300
Output $/1M$25.00$2.50
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
67.16%
55.22%
Avg Response Time4.36s24.91s
Median input tokensincl. image tokens2.0K294
Median output tokens92171
Est. cost / taskon this benchmark$0.012$0.0005
Defect Detection
66.7%(10/15)
60%(9/15)
Document Understanding
77.8%(7/9)
88.9%(8/9)
Object Counting
30%(3/10)
0%(0/10)
Object Understanding
85.7%(12/14)
71.4%(10/14)
Spatial Understanding
68.4%(13/19)
52.6%(10/19)
OCR
Overall Score
87.34%
79.04%
Avg Response Time3.99s2.39s
Median input tokensincl. image tokens578290
Median output tokens8181
Est. cost / taskon this benchmark$0.0049$0.0003
Focused Scene OCR
91.9%(91/99)
79.8%(79/99)
Handwritten Math
60%(6/10)
80%(8/10)
License Plate Recognition
90%(27/30)
90%(27/30)
Text Recognition
86.7%(26/30)
80%(24/30)
VQA & Extraction
83.3%(50/60)
71.7%(43/60)

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