Model Comparison

Gemini 3 Pro vs Gemma 3 27BWhich is better in 2026?

Gemini 3 Pro shows notably better performance in the majority of benchmarks. Gemma 3 27B is 36.0x cheaper per token.

Verdict: Gemini 3 Pro vs Gemma 3 27B — which is better?

Gemini 3 Pro (by Google) and Gemma 3 27B (by Google) 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.

Gemini 3 Pro outperforms in 2 benchmarks (GPQA, SimpleQA), while Gemma 3 27B is better at 1 benchmark (FACTS Grounding). Gemini 3 Pro shows notably better performance in the majority of benchmarks.

On price, Gemma 3 27B is roughly 36.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Gemini 3 Pro also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.

Choose Gemini 3 Pro if…

  • you want the strongest raw capability — it leads on 2 of 3 shared benchmarks
  • you process long inputs — it offers a 1,048,576 token context window
  • you want the most recent training data — it shipped Nov 2025

Choose Gemma 3 27B if…

  • cost matters — it's about 36.0x cheaper per token
  • you need open weights you can self-host or fine-tune
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Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

Gemini 3 Pro outperforms in 2 benchmarks (GPQA, SimpleQA), while Gemma 3 27B is better at 1 benchmark (FACTS Grounding).

Gemini 3 Pro shows notably better performance in the majority of benchmarks.

Thu Jun 25 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Gemma 3 27B costs less

For input processing, Gemini 3 Pro ($2.00/1M tokens) is 20.0x more expensive than Gemma 3 27B ($0.10/1M tokens).

For output processing, Gemini 3 Pro ($12.00/1M tokens) is 60.0x more expensive than Gemma 3 27B ($0.20/1M tokens).

In conclusion, Gemini 3 Pro is more expensive than Gemma 3 27B.*

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

Lowest available price from all providers
Thu Jun 25 2026 • llm-stats.com
Google
Gemini 3 Pro
Input tokens$2.00
Output tokens$12.00
Best providerGoogle
Google
Gemma 3 27B
Input tokens$0.10
Output tokens$0.20
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

Gemini 3 Pro accepts 1,048,576 input tokens compared to Gemma 3 27B's 131,072 tokens. Gemma 3 27B can generate longer responses up to 131,072 tokens, while Gemini 3 Pro is limited to 65,536 tokens.

Google
Gemini 3 Pro
Input1,048,576 tokens
Output65,536 tokens
Google
Gemma 3 27B
Input131,072 tokens
Output131,072 tokens
Thu Jun 25 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both Gemini 3 Pro and Gemma 3 27B support multimodal inputs.

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

Gemini 3 Pro

Text
Images
Audio
Video

Gemma 3 27B

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 3 Pro is licensed under a proprietary license, while Gemma 3 27B uses Gemma.

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

Gemini 3 Pro

Proprietary

Closed source

Gemma 3 27B

Gemma

Open weights

Release Timeline

When each model was launched

Gemini 3 Pro was released on 2025-11-18, while Gemma 3 27B was released on 2025-03-12.

Gemini 3 Pro is 8 months newer than Gemma 3 27B.

Gemini 3 Pro

Nov 18, 2025

7 months ago

8mo newer
Gemma 3 27B

Mar 12, 2025

1.3 years ago

Knowledge Cutoff

When training data ends

Gemini 3 Pro has a documented knowledge cutoff of 2025-01-31, while Gemma 3 27B's cutoff date is not specified.

We can confirm Gemini 3 Pro's training data extends to 2025-01-31, but cannot make a direct comparison without Gemma 3 27B's cutoff date.

Gemini 3 Pro

Jan 2025

Gemma 3 27B

—

Provider Availability

Gemini 3 Pro is available from Google. Gemma 3 27B is available from DeepInfra, Novita.

Gemini 3 Pro

google logo
Google
Input Price:Input: $2.00/1MOutput Price:Output: $12.00/1M

Gemma 3 27B

deepinfra logo
Deepinfra
Input Price:Input: $0.10/1MOutput Price:Output: $0.20/1M
novita logo
Novita
Input Price:Input: $0.11/1MOutput Price:Output: $0.20/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

Google
Larger context window (1,048,576 tokens)
Higher GPQA score (91.9% vs 42.4%)
Higher SimpleQA score (72.1% vs 10.0%)
Google
Less expensive input tokens
Less expensive output tokens
Has open weights
Higher FACTS Grounding score (74.9% vs 70.5%)

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemini 3 Pro
Google
Gemma 3 27B

FAQ

Common questions about Gemini 3 Pro vs Gemma 3 27B.

Which is better, Gemini 3 Pro or Gemma 3 27B?

Gemini 3 Pro shows notably better performance in the majority of benchmarks. Gemini 3 Pro is made by Google and Gemma 3 27B is made by Google. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Gemini 3 Pro compare to Gemma 3 27B in benchmarks?

Gemini 3 Pro scores AIME 2025: 100.0%, Vending-Bench 2: 100.0%, Global PIQA: 93.4%, GPQA: 91.9%, MMMLU: 91.8%. Gemma 3 27B scores GSM8k: 95.9%, IFEval: 90.4%, MATH: 89.0%, HumanEval: 87.8%, BIG-Bench Hard: 87.6%.

Is Gemini 3 Pro cheaper than Gemma 3 27B?

Gemma 3 27B is 20.0x cheaper for input tokens. Gemini 3 Pro costs $2.00/M input and $12.00/M output via google. Gemma 3 27B costs $0.10/M input and $0.20/M output via deepinfra.

What are the context window sizes for Gemini 3 Pro and Gemma 3 27B?

Gemini 3 Pro supports 1.0M tokens and Gemma 3 27B supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemini 3 Pro and Gemma 3 27B?

Key differences include context window (1.0M vs 131K), input pricing ($2.00 vs $0.10/M), licensing (Proprietary vs Gemma). See the full comparison above for benchmark-by-benchmark results.

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