Model Comparison

GPT-4o vs GPT-5 nano

GPT-5 nano significantly outperforms across most benchmarks. GPT-5 nano is 31.8x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

GPT-4o outperforms in 0 benchmarks, while GPT-5 nano is better at 1 benchmark (GPQA).

GPT-5 nano significantly outperforms across most benchmarks.

Thu Apr 09 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

GPT-5 nano costs less

For input processing, GPT-4o ($2.50/1M tokens) is 50.0x more expensive than GPT-5 nano ($0.05/1M tokens).

For output processing, GPT-4o ($10.00/1M tokens) is 25.0x more expensive than GPT-5 nano ($0.40/1M tokens).

In conclusion, GPT-4o is more expensive than GPT-5 nano.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Thu Apr 09 2026 • llm-stats.com
OpenAI
GPT-4o
Input tokens$2.50
Output tokens$10.00
Best providerAzure
OpenAI
GPT-5 nano
Input tokens$0.05
Output tokens$0.40
Best providerOpenAI
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

GPT-5 nano accepts 400,000 input tokens compared to GPT-4o's 128,000 tokens. GPT-5 nano can generate longer responses up to 128,000 tokens, while GPT-4o is limited to 4,096 tokens.

OpenAI
GPT-4o
Input128,000 tokens
Output4,096 tokens
OpenAI
GPT-5 nano
Input400,000 tokens
Output128,000 tokens
Thu Apr 09 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both GPT-4o and GPT-5 nano support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

GPT-4o

Text
Images
Audio
Video

GPT-5 nano

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under proprietary licenses.

Both models have usage restrictions defined by their respective organizations.

GPT-4o

Proprietary

Closed source

GPT-5 nano

Proprietary

Closed source

Release Timeline

When each model was launched

GPT-4o was released on 2024-05-13, while GPT-5 nano was released on 2025-08-07.

GPT-5 nano is 15 months newer than GPT-4o.

GPT-4o

May 13, 2024

1.9 years ago

GPT-5 nano

Aug 7, 2025

8 months ago

1.2yr newer

Knowledge Cutoff

When training data ends

GPT-5 nano has a documented knowledge cutoff of 2024-05-30, while GPT-4o's cutoff date is not specified.

We can confirm GPT-5 nano's training data extends to 2024-05-30, but cannot make a direct comparison without GPT-4o's cutoff date.

GPT-4o

—

GPT-5 nano

May 2024

Provider Availability

GPT-4o is available from Azure, OpenAI. GPT-5 nano is available from OpenAI.

GPT-4o

azure logo
Azure
Input Price:Input: $2.50/1MOutput Price:Output: $10.00/1M
openai logo
OpenAI
Input Price:Input: $2.50/1MOutput Price:Output: $10.00/1M

GPT-5 nano

openai logo
OpenAI
Input Price:Input: $0.05/1MOutput Price:Output: $0.40/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

OpenAI
OpenAI
Larger context window (400,000 tokens)
Less expensive input tokens
Less expensive output tokens
Higher GPQA score (71.2% vs 53.6%)
OpenAIGPT-4o
OpenAIGPT-5 nano
Compare in Playground

Detailed Comparison

AI Model Comparison Table
Feature
OpenAI
GPT-4o
OpenAI
GPT-5 nano

FAQ

Common questions about GPT-4o vs GPT-5 nano

GPT-5 nano significantly outperforms across most benchmarks. GPT-4o is made by OpenAI and GPT-5 nano is made by OpenAI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
GPT-4o scores MGSM: 90.5%, HumanEval: 90.2%, MMLU: 88.7%, DROP: 83.4%, MATH: 76.6%. GPT-5 nano scores AIME 2025: 85.2%, HMMT 2025: 75.6%, GPQA: 71.2%, FrontierMath: 9.6%, Humanity's Last Exam: 8.7%.
GPT-5 nano is 50.0x cheaper for input tokens. GPT-4o costs $2.50/M input and $10.00/M output via azure. GPT-5 nano costs $0.05/M input and $0.40/M output via openai.
GPT-4o supports 128K tokens and GPT-5 nano supports 400K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (128K vs 400K), input pricing ($2.50 vs $0.05/M). See the full comparison above for benchmark-by-benchmark results.