Claude Opus 4.1 vs GPT-5 Nano

Compare Claude Opus 4.1 and GPT-5 Nano side-by-side. See how these vision models stack up in Open Prompt, Classification, Object Detection, OCR, and Image Captioning.

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AnthropicClaude Opus 4.1
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OpenAIGPT-5 Nano
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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.

On benchmarks, Opus 4.1 improves coding performance, reaching ~74.5% on SWE-Bench Verified compared to Opus 4’s ~72.5%. 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.

Claude Opus 4.1 vs GPT-5 Nano Comparison Table

PropertyClaude Opus 4.1GPT-5 Nano
OrganizationAnthropicOpenAI
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateAug 2025Aug 2025
Context Window200K400K
Parameters
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$15.00$0.050
Output $/1M$75.00$0.400
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
59.7%
58.21%
Avg Response Time7.09s6.58s
Median input tokensincl. image tokens2.0K1.8K
Median output tokens140591
Est. cost / taskon this benchmark$0.040$0.0003
Defect Detection
73.3%(11/15)
86.7%(13/15)
Document Understanding
88.9%(8/9)
66.7%(6/9)
Object Counting
0%(0/10)
0%(0/10)
Object Understanding
64.3%(9/14)
64.3%(9/14)
Spatial Understanding
63.2%(12/19)
57.9%(11/19)
OCR
Overall Score
68.56%
69%
Avg Response Time5.08s6.15s
Median input tokensincl. image tokens552122
Median output tokens97539
Est. cost / taskon this benchmark$0.016$0.0002
Focused Scene OCR
73.7%(73/99)
64.6%(64/99)
Handwritten Math
30%(3/10)
40%(4/10)
License Plate Recognition
53.3%(16/30)
83.3%(25/30)
Text Recognition
80%(24/30)
70%(21/30)
VQA & Extraction
68.3%(41/60)
73.3%(44/60)

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