Model Comparison

Gemini 1.0 Pro vs Gemma 2 9BWhich is better in 2026?

Gemini 1.0 Pro shows notably better performance in the majority of benchmarks.

Verdict: Gemini 1.0 Pro vs Gemma 2 9B — which is better?

Gemini 1.0 Pro (by Google) and Gemma 2 9B (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 1.0 Pro outperforms in 2 benchmarks (BIG-Bench, MMLU), while Gemma 2 9B is better at 1 benchmark (MATH). Gemini 1.0 Pro shows notably better performance in the majority of benchmarks.

Choose Gemini 1.0 Pro if…

  • you want the strongest raw capability — it leads on 2 of 3 shared benchmarks

Choose Gemma 2 9B if…

  • you want the most recent training data — it shipped Jun 2024
  • you need open weights you can self-host or fine-tune

Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

Gemini 1.0 Pro outperforms in 2 benchmarks (BIG-Bench, MMLU), while Gemma 2 9B is better at 1 benchmark (MATH).

Gemini 1.0 Pro shows notably better performance in the majority of benchmarks.

Fri Jun 26 2026 • llm-stats.com

Arena Performance

Human preference votes

Context Window

Maximum input and output token capacity

Only Gemini 1.0 Pro specifies input context (32,760 tokens). Only Gemini 1.0 Pro specifies output context (8,192 tokens).

Google
Gemini 1.0 Pro
Input32,760 tokens
Output8,192 tokens
Google
Gemma 2 9B
Input- tokens
Output- tokens
Fri Jun 26 2026 • llm-stats.com

License

Usage and distribution terms

Gemini 1.0 Pro is licensed under a proprietary license, while Gemma 2 9B uses Gemma.

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

Gemini 1.0 Pro

Proprietary

Closed source

Gemma 2 9B

Gemma

Open weights

Release Timeline

When each model was launched

Gemini 1.0 Pro was released on 2024-02-15, while Gemma 2 9B was released on 2024-06-27.

Gemma 2 9B is 4 months newer than Gemini 1.0 Pro.

Gemini 1.0 Pro

Feb 15, 2024

2.4 years ago

Gemma 2 9B

Jun 27, 2024

2.0 years ago

4mo newer

Knowledge Cutoff

When training data ends

Gemini 1.0 Pro has a documented knowledge cutoff of 2024-02-01, while Gemma 2 9B's cutoff date is not specified.

We can confirm Gemini 1.0 Pro's training data extends to 2024-02-01, but cannot make a direct comparison without Gemma 2 9B's cutoff date.

Gemini 1.0 Pro

Feb 2024

Gemma 2 9B

—

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Google
Larger context window (32,760 tokens)
Higher BIG-Bench score (75.0% vs 68.2%)
Higher MMLU score (71.8% vs 71.3%)
Google
Has open weights
Higher MATH score (36.6% vs 32.6%)

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against Gemini 1.0 Pro and Gemma 2 9B side-by-side, then vote on the output you prefer.

Gemini 1.0 Pro
✓ Preferred
Gemma 2 9B
Open in Playground
AI Model Comparison Table
Feature
Google
Gemini 1.0 Pro
Google
Gemma 2 9B

FAQ

Common questions about Gemini 1.0 Pro vs Gemma 2 9B.

Which is better, Gemini 1.0 Pro or Gemma 2 9B?

Gemini 1.0 Pro shows notably better performance in the majority of benchmarks. Gemini 1.0 Pro is made by Google and Gemma 2 9B is made by Google. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Gemini 1.0 Pro compare to Gemma 2 9B in benchmarks?

Gemini 1.0 Pro scores FLEURS: 93.6%, BIG-Bench: 75.0%, MMLU: 71.8%, WMT23: 71.7%, EgoSchema: 55.7%. Gemma 2 9B scores ARC-E: 88.0%, BoolQ: 84.2%, HellaSwag: 81.9%, PIQA: 81.7%, Winogrande: 80.6%.

What are the context window sizes for Gemini 1.0 Pro and Gemma 2 9B?

Gemini 1.0 Pro supports 33K tokens and Gemma 2 9B supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemini 1.0 Pro and Gemma 2 9B?

Key differences include licensing (Proprietary vs Gemma). See the full comparison above for benchmark-by-benchmark results.

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