Claude Opus 4 vs GPT-5 Nano

Compare Claude Opus 4 and GPT-5 Nano side-by-side. See how these vision models stack up in Image Captioning, OCR, Object Detection, Open Prompt, and Classification.

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AnthropicClaude Opus 4

Claude Opus 4 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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Models in this comparison

Anthropic

Claude Opus 4 vs GPT-5 Nano: Overview

Claude Opus 4

Claude 4 Opus, released by Anthropic in May 2025, is the flagship model of the Claude 4 family, built for complex, long-horizon reasoning and advanced coding workflows. It is multimodal, supporting text (including voice), images, and tool use, and operates as a hybrid reasoning model—able to deliver quick answers in fast mode or switch to extended thinking for deeper, multi-step problem solving. With a ~200,000-token context window and a training cutoff around March 2025, it is optimized for handling large documents, long conversations, and sophisticated agentic tasks.

Positioned at the high end of Anthropic’s offerings, Opus 4 achieves state-of-the-art results on coding benchmarks like SWE-Bench (72.5%) and Terminal-Bench (43.2%). It is best suited for research, enterprise automation, and software development at scale. The model is classified at Anthropic’s ASL-3 safety level, denoting advanced oversight and safety features.

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 vs GPT-5 Nano Comparison Table

PropertyClaude Opus 4GPT-5 Nano
OrganizationAnthropicOpenAI
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateMay 2025Aug 2025
Context Window200K400K
Parameters
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$15.00$0.050
Output $/1M$75.00$0.400
Vision Tasks
CaptioningDemo
ClassificationDemo
Object DetectionDemo
OCRDemo
Vision Language
Visual Question AnsweringDemo
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
56.72%
58.21%
Avg Response Time19.74s6.58s
Median input tokensincl. image tokens1.8K
Median output tokens591
Est. cost / taskon this benchmark$0.0003
Defect Detection
66.7%(10/15)
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
57.9%(11/19)
57.9%(11/19)
OCR
Overall Score
69%
Avg Response Time6.15s
Median input tokensincl. image tokens122
Median output tokens539
Est. cost / taskon this benchmark$0.0002
Focused Scene OCR
64.6%(64/99)
Handwritten Math
40%(4/10)
License Plate Recognition
83.3%(25/30)
Text Recognition
70%(21/30)
VQA & Extraction
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