Model Comparison

Gemma 3 12B vs GPT-5 nanoWhich is better in 2026?

GPT-5 nano significantly outperforms across most benchmarks. Gemma 3 12B is 2.2x cheaper per token.

Verdict: Gemma 3 12B vs GPT-5 nano — which is better?

Gemma 3 12B (by Google) and GPT-5 nano (by OpenAI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

Gemma 3 12B outperforms in 0 benchmarks, while GPT-5 nano is better at 1 benchmark (GPQA). GPT-5 nano significantly outperforms across most benchmarks.

On price, Gemma 3 12B is roughly 2.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

GPT-5 nano also accepts a larger context window (400,000 input tokens), making it the stronger choice for long documents and large codebases.

Choose Gemma 3 12B if…

  • cost matters — it's about 2.2x cheaper per token
  • you need open weights you can self-host or fine-tune

Choose GPT-5 nano if…

  • you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
  • you process long inputs — it offers a 400,000 token context window
  • you want the most recent training data — it shipped Aug 2025
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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

Gemma 3 12B outperforms in 0 benchmarks, while GPT-5 nano is better at 1 benchmark (GPQA).

GPT-5 nano significantly outperforms across most benchmarks.

Sat Jun 13 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Gemma 3 12B costs less

For input processing, Gemma 3 12B ($0.05/1M tokens) costs the same as GPT-5 nano ($0.05/1M tokens).

For output processing, Gemma 3 12B ($0.10/1M tokens) is 4.0x cheaper than GPT-5 nano ($0.40/1M tokens).

In conclusion, GPT-5 nano is more expensive than Gemma 3 12B.*

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

Lowest available price from all providers
Sat Jun 13 2026 • llm-stats.com
Google
Gemma 3 12B
Input tokens$0.05
Output tokens$0.10
Best providerDeepinfra
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 Gemma 3 12B's 131,072 tokens. Gemma 3 12B can generate longer responses up to 131,072 tokens, while GPT-5 nano is limited to 128,000 tokens.

Google
Gemma 3 12B
Input131,072 tokens
Output131,072 tokens
OpenAI
GPT-5 nano
Input400,000 tokens
Output128,000 tokens
Sat Jun 13 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Gemma 3 12B and GPT-5 nano support multimodal inputs.

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

Gemma 3 12B

Text
Images
Audio
Video

GPT-5 nano

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 3 12B is licensed under Gemma, while GPT-5 nano uses a proprietary license.

License differences may affect how you can use these models in commercial or open-source projects.

Gemma 3 12B

Gemma

Open weights

GPT-5 nano

Proprietary

Closed source

Release Timeline

When each model was launched

Gemma 3 12B was released on 2025-03-12, while GPT-5 nano was released on 2025-08-07.

GPT-5 nano is 5 months newer than Gemma 3 12B.

Gemma 3 12B

Mar 12, 2025

1.3 years ago

GPT-5 nano

Aug 7, 2025

10 months ago

4mo newer

Knowledge Cutoff

When training data ends

GPT-5 nano has a documented knowledge cutoff of 2024-05-30, while Gemma 3 12B'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 Gemma 3 12B's cutoff date.

Gemma 3 12B

—

GPT-5 nano

May 2024

Provider Availability

Gemma 3 12B is available from DeepInfra. GPT-5 nano is available from OpenAI.

Gemma 3 12B

deepinfra logo
Deepinfra
Input Price:Input: $0.05/1MOutput Price:Output: $0.10/1M

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

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Google
Less expensive output tokens
Has open weights
OpenAI
Larger context window (400,000 tokens)
Higher GPQA score (71.2% vs 40.9%)

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemma 3 12B
OpenAI
GPT-5 nano

FAQ

Common questions about Gemma 3 12B vs GPT-5 nano.

Which is better, Gemma 3 12B or GPT-5 nano?

GPT-5 nano significantly outperforms across most benchmarks. Gemma 3 12B is made by Google and GPT-5 nano is made by OpenAI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Gemma 3 12B compare to GPT-5 nano in benchmarks?

Gemma 3 12B scores GSM8k: 94.4%, IFEval: 88.9%, DocVQA: 87.1%, BIG-Bench Hard: 85.7%, HumanEval: 85.4%. GPT-5 nano scores AIME 2025: 85.2%, HMMT 2025: 75.6%, GPQA: 71.2%, FrontierMath: 9.6%, Humanity's Last Exam: 8.7%.

Is Gemma 3 12B cheaper than GPT-5 nano?

Both models cost $0.05 per million input tokens.

What are the context window sizes for Gemma 3 12B and GPT-5 nano?

Gemma 3 12B supports 131K tokens and GPT-5 nano supports 400K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemma 3 12B and GPT-5 nano?

Key differences include context window (131K vs 400K), licensing (Gemma vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemma 3 12B and GPT-5 nano?

Gemma 3 12B is developed by Google and GPT-5 nano is developed by OpenAI.

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