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Gemini 3.8 Flash Cyber vs GLM-4.5V

Comparing Gemini 3.8 Flash Cyber and GLM-4.5V across benchmarks, pricing, and capabilities.

Google · Zhipu AI · Updated for 2026

Which is better?

Gemini 3.8 Flash Cyber and GLM-4.5V 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 GLM-4.5V

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

At a glance

The differences that matter most.

Gemini 3.8 Flash Cyber
Google
GLM-4.5V
Zhipu AI
Benchmark wins
—
—
Input price
— / M
$0.55 / M
Output price
— / M
$2.19 / M
Context window
—
131,072

Individual benchmarks

4 reported for Gemini 3.8 Flash Cyber · 0 for GLM-4.5V

No common benchmarks found

Gemini 3.8 Flash Cyber and GLM-4.5Vdon'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 GLM-4.5V specifies input context (131,072 tokens). Only GLM-4.5V specifies output context (131,072 tokens).

Google
Gemini 3.8 Flash Cyber
Input- tokens
Output- tokens
Zhipu AI
GLM-4.5V
Input131,072 tokens
Output131,072 tokens
Sat Sep 05 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

GLM-4.5V supports multimodal inputs, whereas Gemini 3.8 Flash Cyber does not.

GLM-4.5V 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

GLM-4.5V

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 3.8 Flash Cyber is licensed under a proprietary license, while GLM-4.5V uses MIT.

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

Gemini 3.8 Flash Cyber

Proprietary

Closed source

GLM-4.5V

MIT

Open weights

Release Timeline

When each model was launched

Gemini 3.8 Flash Cyber was released on 2026-09-02, while GLM-4.5V was released on 2025-08-11.

Gemini 3.8 Flash Cyber is 13 months newer than GLM-4.5V.

Gemini 3.8 Flash Cyber

Sep 2, 2026

3 days ago

1.1yr newer
GLM-4.5V

Aug 11, 2025

1.1 years ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

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 GLM-4.5V side-by-side, then vote on the output you prefer.

Gemini 3.8 Flash Cyber
✓ Preferred
GLM-4.5V
Open in Playground

FAQ

Common questions about Gemini 3.8 Flash Cyber vs GLM-4.5V.

Which is better, Gemini 3.8 Flash Cyber or GLM-4.5V?

Gemini 3.8 Flash Cyber (Google) and GLM-4.5V (Zhipu AI) 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 GLM-4.5V 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 GLM-4.5V?

Gemini 3.8 Flash Cyber supports an unknown number of tokens and GLM-4.5V 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 3.8 Flash Cyber and GLM-4.5V?

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

Who makes Gemini 3.8 Flash Cyber and GLM-4.5V?

Gemini 3.8 Flash Cyber is developed by Google and GLM-4.5V is developed by Zhipu AI.

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