Model Comparison

GLM-5 vs Gemma 3n E4BWhich is better in 2026?

Comparing GLM-5 and Gemma 3n E4B across benchmarks, pricing, and capabilities.

Verdict: GLM-5 vs Gemma 3n E4B — which is better?

GLM-5 (by Zhipu AI) and Gemma 3n E4B (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.

Choose GLM-5 if…

  • you want the most recent training data — it shipped Feb 2026
  • you need open weights you can self-host or fine-tune

Choose Gemma 3n E4B if…

  • you are already invested in the Google ecosystem
Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5 and Gemma 3n E4B don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Model Size

Parameter count comparison

736.0B diff

GLM-5 has 736.0B more parameters than Gemma 3n E4B, making it 9200.0% larger.

Zhipu AI
GLM-5
744.0Bparameters
Google
Gemma 3n E4B
8.0Bparameters
744.0B
GLM-5
8.0B
Gemma 3n E4B

Context Window

Maximum input and output token capacity

Only GLM-5 specifies input context (200,000 tokens). Only GLM-5 specifies output context (128,000 tokens).

Zhipu AI
GLM-5
Input200,000 tokens
Output128,000 tokens
Google
Gemma 3n E4B
Input- tokens
Output- tokens
Sun Jun 07 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemma 3n E4B supports multimodal inputs, whereas GLM-5 does not.

Gemma 3n E4B can handle both text and other forms of data like images, making it suitable for multimodal applications.

GLM-5

Text
Images
Audio
Video

Gemma 3n E4B

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-5 is licensed under MIT, while Gemma 3n E4B uses a proprietary license.

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

GLM-5

MIT

Open weights

Gemma 3n E4B

Proprietary

Closed source

Release Timeline

When each model was launched

GLM-5 was released on 2026-02-11, while Gemma 3n E4B was released on 2025-06-26.

GLM-5 is 8 months newer than Gemma 3n E4B.

GLM-5

Feb 11, 2026

3 months ago

7mo newer
Gemma 3n E4B

Jun 26, 2025

11 months ago

Knowledge Cutoff

When training data ends

Gemma 3n E4B has a documented knowledge cutoff of 2024-06-01, while GLM-5's cutoff date is not specified.

We can confirm Gemma 3n E4B's training data extends to 2024-06-01, but cannot make a direct comparison without GLM-5's cutoff date.

GLM-5

—

Gemma 3n E4B

Jun 2024

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Zhipu AI
Larger context window (200,000 tokens)
Has open weights
Google
Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
Zhipu AI
GLM-5
Google
Gemma 3n E4B

FAQ

Common questions about GLM-5 vs Gemma 3n E4B.

Which is better, GLM-5 or Gemma 3n E4B?

GLM-5 (Zhipu AI) and Gemma 3n E4B (Google) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does GLM-5 compare to Gemma 3n E4B in benchmarks?

GLM-5 scores t2-bench: 89.7%, SWE-Bench Verified: 77.8%, BrowseComp: 75.9%, MCP Atlas: 67.8%, Terminal-Bench 2.0: 56.2%. Gemma 3n E4B scores ARC-E: 81.6%, BoolQ: 81.6%, PIQA: 81.0%, HellaSwag: 78.6%, Winogrande: 71.7%.

What are the context window sizes for GLM-5 and Gemma 3n E4B?

GLM-5 supports 200K tokens and Gemma 3n E4B 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 GLM-5 and Gemma 3n E4B?

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

Who makes GLM-5 and Gemma 3n E4B?

GLM-5 is developed by Zhipu AI and Gemma 3n E4B is developed by Google.

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