Model Comparison

GPT-4o mini vs GPT-5 nano

GPT-5 nano significantly outperforms across most benchmarks. GPT-5 nano is 1.9x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

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

GPT-5 nano significantly outperforms across most benchmarks.

Mon Apr 27 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 mini ($0.15/1M tokens) is 3.0x more expensive than GPT-5 nano ($0.05/1M tokens).

For output processing, GPT-4o mini ($0.60/1M tokens) is 1.5x more expensive than GPT-5 nano ($0.40/1M tokens).

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

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

Lowest available price from all providers
Mon Apr 27 2026 • llm-stats.com
OpenAI
GPT-4o mini
Input tokens$0.15
Output tokens$0.60
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 mini's 128,000 tokens. GPT-5 nano can generate longer responses up to 128,000 tokens, while GPT-4o mini is limited to 16,384 tokens.

OpenAI
GPT-4o mini
Input128,000 tokens
Output16,384 tokens
OpenAI
GPT-5 nano
Input400,000 tokens
Output128,000 tokens
Mon Apr 27 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

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

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

GPT-4o mini

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 mini

Proprietary

Closed source

GPT-5 nano

Proprietary

Closed source

Release Timeline

When each model was launched

GPT-4o mini was released on 2024-07-18, while GPT-5 nano was released on 2025-08-07.

GPT-5 nano is 13 months newer than GPT-4o mini.

GPT-4o mini

Jul 18, 2024

1.8 years ago

GPT-5 nano

Aug 7, 2025

8 months ago

1.1yr newer

Knowledge Cutoff

When training data ends

GPT-4o mini has a knowledge cutoff of 2023-10-01, while GPT-5 nano has a cutoff of 2024-05-30.

GPT-5 nano has more recent training data (up to 2024-05-30), making it potentially better informed about events through that date compared to GPT-4o mini (2023-10-01).

GPT-4o mini

Oct 2023

GPT-5 nano

May 2024

7 mo newer

Provider Availability

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

GPT-4o mini

azure logo
Azure
Input Price:Input: $0.15/1MOutput Price:Output: $0.60/1M

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 40.2%)

Detailed Comparison

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

FAQ

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

GPT-5 nano significantly outperforms across most benchmarks. GPT-4o mini 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 mini scores HumanEval: 87.2%, MGSM: 87.0%, MMLU: 82.0%, DROP: 79.7%, MATH: 70.2%. 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 3.0x cheaper for input tokens. GPT-4o mini costs $0.15/M input and $0.60/M output via azure. GPT-5 nano costs $0.05/M input and $0.40/M output via openai.
GPT-4o mini 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 ($0.15 vs $0.05/M). See the full comparison above for benchmark-by-benchmark results.