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Claude Opus 4.8 vs Gemini 3.1 Pro

Gemini 3.1 Pro and Claude Opus 4.8 score 76.8% vs 58.3% averaged across five Vision Evals tasks (#14 and #40 of 65 models), so Gemini 3.1 Pro leads overall.

  • Gemini 3.1 Pro wins all 5 tasks, with its widest lead on object detection (67.4% vs 38.6%).
  • Gemini 3.1 Pro is about half the cost: $0.010 vs $0.021 overall average cost per sample.
  • Claude Opus 4.8 is faster: 7.7s vs 8.4s per sample.

Compare Claude Opus 4.8 vs Gemini 3.1 Pro live

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AnthropicClaude Opus 4.8
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GoogleGemini 3.1 Pro
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Claude Opus 4.8 vs Gemini 3.1 Pro on Vision Evals

Score by taskClaude Opus 4.8Gemini 3.1 Pro
Object Detection
38.6
67.4
Reasoning
53.0
72.2
Counting
54.0
71.6
Identification
84.4
100.0
OCR
61.5
72.6

Roboflow Vision Evals. Full breakdown below.

Claude Opus 4.8 vs Gemini 3.1 Pro Comparison Table

Evals updated October 26, 2026Pricing updated November 5, 2026

PropertyClaude Opus 4.8Gemini 3.1 Pro
OrganizationAnthropicGoogle
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateMay 2026Feb 2026
Context Window1.0M1.0M
ParametersUnknownUnknown
LicenseProprietaryProprietary
Commercial usecommercial use per vendor termscommercial use per vendor terms
Pricing per 1M tokens
Input $/1M$5.00$2.00
Output $/1M$25.00$12.00
Vision Tasks
Both support 10 more tasks
Model Features
Both support 3 more features
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort
Overall
58.3%
76.8%
Avg cost / sample$0.021$0.010
Avg speed / sample7.66s8.44s
By task
Object Detection
38.6%
$0.026
67.4%
$0.010
Counting
54.0%
$0.0076
71.6%
$0.0071
Identification
84.4%
$0.0067
100.0%
$0.0070
OCR (low)
61.5%
$0.025
72.6%
$0.010
by category
Single value
53.0%
Transcription
70.8%
Structured JSON
82.4%
Text localization
24.2%
Single value
67.8%
Transcription
88.5%
Structured JSON
82.0%
Text localization
52.0%
OCR (high)
62.1%
$0.038
73.1%
$0.026
by category
Single value
54.8%
Transcription
67.0%
Structured JSON
83.5%
Text localization
23.6%
Single value
68.7%
Transcription
90.8%
Structured JSON
83.9%
Text localization
47.1%
Reasoning (low)
53.0%
$0.0078
72.2%
$0.012
Reasoning (high)
52.3%
$0.0078
74.8%
$0.021

Claude Opus 4.8 vs Gemini 3.1 Pro: 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. 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 3.1 Pro

Gemini 3.1 Pro is a proprietary multimodal model from Google’s Gemini 3 series, released in early 2026 and designed for advanced reasoning across large multimodal datasets. It accepts text, images, audio, video, and documents, supporting up to a 1-million-token input context with up to 64k output tokens. Compared with Gemini 3 Pro, it improves long-context synthesis and multi-step reasoning, enabling more reliable analysis of large documents, datasets, and software codebases.

The model also advances visual understanding and grounding, allowing it to interpret UI screenshots, diagrams, and real-world scenes while referencing specific regions within images or video. These capabilities make Gemini 3.1 Pro well suited for multimodal workflows involving document processing, interface analysis, robotics research, and complex visual reasoning.

Frequently Asked Questions

On Roboflow's Vision Evals, Gemini 3.1 Pro performed better. It scores higher on all five vision tasks and averages 76.8% (#14 of 65) against 58.3% (#40 of 65) for Claude Opus 4.8. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.

No. On the Vision Evals Object Detection benchmark at low effort, Gemini 3.1 Pro leads with 67.4% against 38.6%. This is the widest gap between the two models across the benchmark's tasks.

Gemini 3.1 Pro is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.010 per sample against $0.021. Claude Opus 4.8 is priced at $5.00 per 1M input tokens and $25.00 per 1M output; Gemini 3.1 Pro is priced at $2.00 per 1M input tokens and $12.00 per 1M output. Actual costs depend on your image sizes, prompts, and output length.

Claude Opus 4.8 is faster. Across Roboflow's Vision Evals it averaged 7.7s per inference against 8.4s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.

Yes. The comparison demo on this page runs both models on the same image side by side for image captioning and image classification in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.