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Gemma 3n E4B vs GLM-4.5

GLM-4.5 leads the LLM Stats Score 28.0 to -6.0.

Google · Zhipu AI · Updated for 2026

Which is better?

GLM-4.5 leads the overall LLM Stats Score 28.0 to -6.0, ranking #128 overall.

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

Choose Gemma 3n E4B

  • you are already invested in the Google ecosystem

Choose GLM-4.5

  • overall performance matters — it scores 28.0 and ranks #128 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Jul 2025
  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Gemma 3n E4B
Google
GLM-4.5
Zhipu AI
Core performance indexes
LLM Stats Score
-6.0
#350
28.0
#128
Reasoning
-6.3
#340
27.4
#128
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
$0.40 / M
Output price
— / M
$1.60 / M
Context window
—
131,072

Capability indexes

Additional strengths measured across groups of related public benchmarks

1 shared
Index
Gemma 3n E4B
GLM-4.5
Math
-2.5#303
27.0#95
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

11 reported for Gemma 3n E4B · 14 for GLM-4.5

No common benchmarks found

Gemma 3n E4B and GLM-4.5don'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

Model Size

Parameter count comparison

347.0B diff

GLM-4.5 has 347.0B more parameters than Gemma 3n E4B, making it 4337.5% larger.

Google
Gemma 3n E4B
8.0Bparameters
Zhipu AI
GLM-4.5
355.0Bparameters
8.0B
Gemma 3n E4B
355.0B
GLM-4.5

Context Window

Maximum input and output token capacity

Only GLM-4.5 specifies input context (131,072 tokens). Only GLM-4.5 specifies output context (131,072 tokens).

Google
Gemma 3n E4B
Input- tokens
Output- tokens
Zhipu AI
GLM-4.5
Input131,072 tokens
Output131,072 tokens
Sun Sep 06 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Gemma 3n E4B supports multimodal inputs, whereas GLM-4.5 does not.

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

Gemma 3n E4B

Text
Images
Audio
Video

GLM-4.5

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 3n E4B is licensed under a proprietary license, while GLM-4.5 uses MIT.

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

Gemma 3n E4B

Proprietary

Closed source

GLM-4.5

MIT

Open weights

Release Timeline

When each model was launched

Gemma 3n E4B was released on 2025-06-26, while GLM-4.5 was released on 2025-07-28.

GLM-4.5 is 1 month newer than Gemma 3n E4B.

Gemma 3n E4B

Jun 26, 2025

1.2 years ago

GLM-4.5

Jul 28, 2025

1.1 years ago

1mo newer

Knowledge Cutoff

When training data ends

Gemma 3n E4B has a documented knowledge cutoff of 2024-06-01, while GLM-4.5'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-4.5's cutoff date.

Gemma 3n E4B

Jun 2024

GLM-4.5

—

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Gemma 3n E4B and GLM-4.5 side-by-side, then vote on the output you prefer.

Gemma 3n E4B
✓ Preferred
GLM-4.5
Open in Playground

FAQ

Common questions about Gemma 3n E4B vs GLM-4.5.

Which is better, Gemma 3n E4B or GLM-4.5?

GLM-4.5 leads the LLM Stats Score 28.0 to -6.0. Gemma 3n E4B is made by Google and GLM-4.5 is made by Zhipu AI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Gemma 3n E4B compare to GLM-4.5 in benchmarks?

Gemma 3n E4B scores ARC-E: 81.6%, BoolQ: 81.6%, PIQA: 81.0%, HellaSwag: 78.6%, Winogrande: 71.7%. GLM-4.5 scores MATH-500: 98.2%, AIME 2024: 91.0%, MMLU-Pro: 84.6%, TAU-bench Retail: 79.7%, GPQA: 79.1%.

What are the context window sizes for Gemma 3n E4B and GLM-4.5?

Gemma 3n E4B supports an unknown number of tokens and GLM-4.5 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 Gemma 3n E4B and GLM-4.5?

Key differences include LLM Stats Score (-6.0 vs 28.0), multimodal support (yes vs no), licensing (Proprietary vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemma 3n E4B and GLM-4.5?

Gemma 3n E4B is developed by Google and GLM-4.5 is developed by Zhipu AI.

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