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Gemini 3.8 Flash Cyber vs o3-pro

Comparing Gemini 3.8 Flash Cyber and o3-pro across benchmarks, pricing, and capabilities.

Google · OpenAI · Updated for 2026

Which is better?

Gemini 3.8 Flash Cyber and o3-pro trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

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

Choose Gemini 3.8 Flash Cyber

  • you want the most recent training data — it shipped Sep 2026

Choose o3-pro

  • you want predictable pricing at $20.00/M input and $80.00/M output

At a glance

The differences that matter most.

Gemini 3.8 Flash Cyber
Google
o3-pro
OpenAI
Benchmark wins
—
—
Input price
— / M
$20.00 / M
Output price
— / M
$80.00 / M
Context window
—
200,000

Individual benchmarks

4 reported for Gemini 3.8 Flash Cyber · 0 for o3-pro

No common benchmarks found

Gemini 3.8 Flash Cyber and o3-prodon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Context Window

Maximum input and output token capacity

Only o3-pro specifies input context (200,000 tokens). Only o3-pro specifies output context (100,000 tokens).

Google
Gemini 3.8 Flash Cyber
Input- tokens
Output- tokens
OpenAI
o3-pro
Input200,000 tokens
Output100,000 tokens
Sun Sep 13 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

o3-pro supports multimodal inputs, whereas Gemini 3.8 Flash Cyber does not.

o3-pro can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemini 3.8 Flash Cyber

Text
Images
Audio
Video

o3-pro

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.

Gemini 3.8 Flash Cyber

Proprietary

Closed source

o3-pro

Proprietary

Closed source

Release Timeline

When each model was launched

Gemini 3.8 Flash Cyber was released on 2026-09-02, while o3-pro was released on 2025-06-10.

Gemini 3.8 Flash Cyber is 15 months newer than o3-pro.

Gemini 3.8 Flash Cyber

Sep 2, 2026

1 weeks ago

1.2yr newer
o3-pro

Jun 10, 2025

1.3 years ago

Knowledge Cutoff

When training data ends

o3-pro has a documented knowledge cutoff of 2024-05-31, while Gemini 3.8 Flash Cyber's cutoff date is not specified.

We can confirm o3-pro's training data extends to 2024-05-31, but cannot make a direct comparison without Gemini 3.8 Flash Cyber's cutoff date.

Gemini 3.8 Flash Cyber

—

o3-pro

May 2024

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Gemini 3.8 Flash Cyber and o3-pro side-by-side, then vote on the output you prefer.

Gemini 3.8 Flash Cyber
✓ Preferred
o3-pro
Open in Playground

FAQ

Common questions about Gemini 3.8 Flash Cyber vs o3-pro.

Which is better, Gemini 3.8 Flash Cyber or o3-pro?

Gemini 3.8 Flash Cyber (Google) and o3-pro (OpenAI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does Gemini 3.8 Flash Cyber compare to o3-pro in benchmarks?

Gemini 3.8 Flash Cyber scores Gray Swan IPI Benchmark: 94.0%, CyberGym: 86.2%, Google Real-world Vulnerability Discovery: 71.0%, CWE-Bench: 47.2%.

What are the context window sizes for Gemini 3.8 Flash Cyber and o3-pro?

Gemini 3.8 Flash Cyber supports an unknown number of tokens and o3-pro supports 200K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemini 3.8 Flash Cyber and o3-pro?

Key differences include multimodal support (no vs yes). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 3.8 Flash Cyber and o3-pro?

Gemini 3.8 Flash Cyber is developed by Google and o3-pro is developed by OpenAI.

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