Model Comparison

GPT-5 vs GPT-5 nano

GPT-5 significantly outperforms across most benchmarks. GPT-5 nano is 25.0x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

5 benchmarks

GPT-5 outperforms in 5 benchmarks (AIME 2025, FrontierMath, GPQA, HMMT 2025, Humanity's Last Exam), while GPT-5 nano is better at 0 benchmarks.

GPT-5 significantly outperforms across most benchmarks.

Fri May 01 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-5 ($1.25/1M tokens) is 25.0x more expensive than GPT-5 nano ($0.05/1M tokens).

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

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

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

Lowest available price from all providers
Fri May 01 2026 • llm-stats.com
OpenAI
GPT-5
Input tokens$1.25
Output tokens$10.00
Best providerOpenAI
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

Both models have the same input context window of 400,000 tokens. Both models can generate responses up to 128,000 tokens.

OpenAI
GPT-5
Input400,000 tokens
Output128,000 tokens
OpenAI
GPT-5 nano
Input400,000 tokens
Output128,000 tokens
Fri May 01 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

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

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

GPT-5

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-5

Proprietary

Closed source

GPT-5 nano

Proprietary

Closed source

Release Timeline

When each model was launched

Both models were released on 2025-08-07.

They likely represent similar generations of model development.

GPT-5

Aug 7, 2025

8 months ago

GPT-5 nano

Aug 7, 2025

8 months ago

Knowledge Cutoff

When training data ends

GPT-5 has a knowledge cutoff of 2024-09-30, while GPT-5 nano has a cutoff of 2024-05-30.

GPT-5 has more recent training data (up to 2024-09-30), making it potentially better informed about events through that date compared to GPT-5 nano (2024-05-30).

GPT-5

Sep 2024

4 mo newer
GPT-5 nano

May 2024

Provider Availability

GPT-5 is available from OpenAI. GPT-5 nano is available from OpenAI.

GPT-5

openai logo
OpenAI
Input Price:Input: $1.25/1MOutput 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
Higher AIME 2025 score (94.6% vs 85.2%)
Higher FrontierMath score (26.3% vs 9.6%)
Higher GPQA score (85.7% vs 71.2%)
Higher HMMT 2025 score (93.3% vs 75.6%)
Higher Humanity's Last Exam score (24.8% vs 8.7%)
OpenAI
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

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

FAQ

Common questions about GPT-5 vs GPT-5 nano

GPT-5 significantly outperforms across most benchmarks. GPT-5 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-5 scores SWE-Lancer (IC-Diamond subset): 100.0%, COLLIE: 99.0%, Tau2 Telecom: 96.7%, OpenAI-MRCR: 2 needle 128k: 95.2%, AIME 2025: 94.6%. 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 25.0x cheaper for input tokens. GPT-5 costs $1.25/M input and $10.00/M output via openai. GPT-5 nano costs $0.05/M input and $0.40/M output via openai.
GPT-5 supports 400K 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 input pricing ($1.25 vs $0.05/M). See the full comparison above for benchmark-by-benchmark results.