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Gemma 2 27B vs GPT-4.1 nano

Gemma 2 27B and GPT-4.1 nano are closely matched at -0.7 and 1.6 on the LLM Stats Score.

Google · OpenAI · Updated for 2026

Which is better?

Gemma 2 27B and GPT-4.1 nano are closely matched on the overall LLM Stats Score at -0.7 and 1.6.

In the 1 individual benchmarks reported for both models, GPT-4.1 nano wins 1; this is a narrower head-to-head signal than the composite indexes.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Gemma 2 27B

  • you need open weights you can self-host or fine-tune

Choose GPT-4.1 nano

  • you value its reported benchmark strengths — it wins 1 of 1 exact shared results
  • you want the most recent training data — it shipped Apr 2025

At a glance

The differences that matter most.

Core performance indexes
-0.7
#330
1.6
#320
-1.1
#326
2.0
#308
-7.9
#263
-11.8
#266
Cost, coverage & limits
Benchmark wins
0 of 1
1 of 1
Input price
— / M
$0.10 / M
Output price
— / M
$0.40 / M
Context window
1,047,576

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
Gemma 2 27B
GPT-4.1 nano
-0.7#297
5.0#274
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

16 reported for Gemma 2 27B · 24 for GPT-4.1 nano

1 shared

Gemma 2 27B outperforms in 0 benchmarks, while GPT-4.1 nano is better at 1 benchmark (MMLU).

GPT-4.1 nano significantly outperforms across most benchmarks.

Sun Sep 20 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only GPT-4.1 nano specifies input context (1,047,576 tokens). Only GPT-4.1 nano specifies output context (32,768 tokens).

Google
Gemma 2 27B
Input- tokens
Output- tokens
OpenAI
GPT-4.1 nano
Input1,047,576 tokens
Output32,768 tokens
Sun Sep 20 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

GPT-4.1 nano supports multimodal inputs, whereas Gemma 2 27B does not.

GPT-4.1 nano can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemma 2 27B

Text
Images
Audio
Video

GPT-4.1 nano

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 2 27B is licensed under Gemma, while GPT-4.1 nano uses a proprietary license.

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

Gemma 2 27B

Gemma

Open weights

GPT-4.1 nano

Proprietary

Closed source

Release Timeline

When each model was launched

Gemma 2 27B was released on 2024-06-27, while GPT-4.1 nano was released on 2025-04-14.

GPT-4.1 nano is 10 months newer than Gemma 2 27B.

Gemma 2 27B

Jun 27, 2024

2.2 years ago

GPT-4.1 nano

Apr 14, 2025

1.4 years ago

9mo newer

Knowledge Cutoff

When training data ends

GPT-4.1 nano has a documented knowledge cutoff of 2024-05-31, while Gemma 2 27B's cutoff date is not specified.

We can confirm GPT-4.1 nano's training data extends to 2024-05-31, but cannot make a direct comparison without Gemma 2 27B's cutoff date.

Gemma 2 27B

GPT-4.1 nano

May 2024

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against Gemma 2 27B and GPT-4.1 nano side-by-side, then vote on the output you prefer.

Gemma 2 27B
✓ Preferred
GPT-4.1 nano
Open in Playground

FAQ

Common questions about Gemma 2 27B vs GPT-4.1 nano.

Which is better, Gemma 2 27B or GPT-4.1 nano?

Gemma 2 27B and GPT-4.1 nano are closely matched on the LLM Stats Score at -0.7 and 1.6. Gemma 2 27B is made by Google and GPT-4.1 nano is made by OpenAI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Gemma 2 27B compare to GPT-4.1 nano in benchmarks?

Gemma 2 27B scores ARC-E: 88.6%, HellaSwag: 86.4%, BoolQ: 84.8%, TriviaQA: 83.7%, Winogrande: 83.7%. GPT-4.1 nano scores MMLU: 80.1%, IFEval: 74.5%, CharXiv-D: 73.9%, MMMLU: 66.9%, Multi-IF: 57.2%.

What are the context window sizes for Gemma 2 27B and GPT-4.1 nano?

Gemma 2 27B supports an unknown number of tokens and GPT-4.1 nano supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemma 2 27B and GPT-4.1 nano?

Key differences include LLM Stats Score (-0.7 vs 1.6), multimodal support (no vs yes), licensing (Gemma vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemma 2 27B and GPT-4.1 nano?

Gemma 2 27B is developed by Google and GPT-4.1 nano is developed by OpenAI.