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Claude Opus 4.1 vs GPT-5 Nano

We don't benchmark Claude Opus 4.1 or GPT-5 Nano on Vision Evals. Both are proprietary under Proprietary, so commercial use per vendor terms. GPT-5 Nano is cheaper per token ($0.05/M vs $15/M input).

Compare Claude Opus 4.1 vs GPT-5 Nano live

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AnthropicClaude Opus 4.1

Claude Opus 4.1 is deprecated and can no longer be run. Details and evals are still available on its model page.

OpenAIGPT-5 Nano
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Claude Opus 4.1 vs GPT-5 Nano Comparison Table

Pricing updated November 10, 2026

PropertyClaude Opus 4.1GPT-5 Nano
OrganizationAnthropicOpenAI
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateAug 2025Aug 2025
Context Window200K400K
ParametersUnknownUnknown
LicenseProprietaryProprietary
Commercial usecommercial use per vendor termscommercial use per vendor terms
Pricing per 1M tokens
Input $/1M$15.00$0.050
Output $/1M$75.00$0.400
Vision Tasks
CaptioningSupportedDemo
ClassificationSupportedDemo
Object DetectionSupportedDemo
OCRSupportedDemo
Visual Question AnsweringSupportedDemo
Both support 5 more tasks
Model Features
Both support 3 more features

Claude Opus 4.1 vs GPT-5 Nano: Overview

Claude Opus 4.1

Claude 4.1 Opus, released by Anthropic in August 2025, is the upgraded flagship of the Claude 4 family, building on Opus 4 with stronger reasoning and agentic capabilities. Like its predecessor, it is multimodal and optimized for text, code, and tool use, with support for large context windows suited to multi-file codebases, technical workflows, and long-horizon problem solving.

It demonstrates more precise debugging, refactoring, and orchestration of agentic tasks while maintaining similar safety and alignment safeguards. It is best suited for enterprise-scale software development, research automation, and advanced reasoning workflows where reliability and depth of analysis are critical.

GPT-5 Nano

GPT-5 Nano, released by OpenAI on August 7, 2025, is the smallest and most cost-efficient model in the GPT-5 family. Like its larger counterparts, it is multimodal—accepting text and images, supporting tool use, structured outputs, and reasoning—but it is optimized for speed, low latency, and affordability. It features input and output token limits of roughly 272K and 128K tokens respectively, enabling large-context processing even at its compact scale. Its knowledge cutoff is around May 2024, slightly earlier than the full GPT-5 model.

GPT-5 Nano is well-suited for high-volume or cost-sensitive deployments such as mobile apps, embedded AI systems, or rapid-response APIs. While it offers less depth on complex reasoning and coding tasks compared to GPT-5 Mini or Pro, it retains core multimodal and agentic capabilities, making it an attractive option where efficiency and scale matter more than maximum performance.