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Gemma 4 E4B vs GLM-5.3-Flash

GLM-5.3-Flash leads the LLM Stats Score 51.6 to 14.4.

Google · Zhipu AI · Updated for 2026

Which is better?

GLM-5.3-Flash leads the overall LLM Stats Score 51.6 to 14.4, ranking #11 overall.

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

Choose Gemma 4 E4B

  • you are already invested in the Google ecosystem

Choose GLM-5.3-Flash

  • overall performance matters — it scores 51.6 and ranks #11 on LLM Stats
  • your work emphasizes reasoning and agents — it leads those capability indexes
  • you want the most recent training data — it shipped Aug 2026

At a glance

The differences that matter most.

Gemma 4 E4B
Google
GLM-5.3-Flash
Zhipu AI
Core performance indexes
LLM Stats Score
14.4
#218
51.6
#11
Reasoning
14.3
#213
50.3
#13
Agents
2.3
#147
39.1
#9
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
$0.15 / M
Output price
— / M
$0.50 / M
Context window
—
1,048,576

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
Gemma 4 E4B
GLM-5.3-Flash
Vision
4.3#151
32.0#21
Multimodal
6.6#125
30.9#24
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

11 reported for Gemma 4 E4B · 15 for GLM-5.3-Flash

No common benchmarks found

Gemma 4 E4B and GLM-5.3-Flashdon'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

312.0B diff

GLM-5.3-Flash has 312.0B more parameters than Gemma 4 E4B, making it 3900.0% larger.

Google
Gemma 4 E4B
8.0Bparameters
Zhipu AI
GLM-5.3-Flash
320.0Bparameters
8.0B
Gemma 4 E4B
320.0B
GLM-5.3-Flash

Context Window

Maximum input and output token capacity

Only GLM-5.3-Flash specifies input context (1,048,576 tokens). Only GLM-5.3-Flash specifies output context (131,072 tokens).

Google
Gemma 4 E4B
Input- tokens
Output- tokens
Zhipu AI
GLM-5.3-Flash
Input1,048,576 tokens
Output131,072 tokens
Fri Aug 28 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both Gemma 4 E4B and GLM-5.3-Flash support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

Gemma 4 E4B

Text
Images
Audio
Video

GLM-5.3-Flash

Text
Images
Audio
Video

License

Usage and distribution terms

Gemma 4 E4B is licensed under Apache 2.0, while GLM-5.3-Flash uses MIT.

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

Gemma 4 E4B

Apache 2.0

Open weights

GLM-5.3-Flash

MIT

Open weights

Release Timeline

When each model was launched

Gemma 4 E4B was released on 2026-04-02, while GLM-5.3-Flash was released on 2026-08-26.

GLM-5.3-Flash is 5 months newer than Gemma 4 E4B.

Gemma 4 E4B

Apr 2, 2026

4 months ago

GLM-5.3-Flash

Aug 26, 2026

2 days ago

4mo newer

Knowledge Cutoff

When training data ends

Gemma 4 E4B has a documented knowledge cutoff of 2025-01-01, while GLM-5.3-Flash's cutoff date is not specified.

We can confirm Gemma 4 E4B's training data extends to 2025-01-01, but cannot make a direct comparison without GLM-5.3-Flash's cutoff date.

Gemma 4 E4B

Jan 2025

GLM-5.3-Flash

—

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against Gemma 4 E4B and GLM-5.3-Flash side-by-side, then vote on the output you prefer.

Gemma 4 E4B
✓ Preferred
GLM-5.3-Flash
Open in Playground

FAQ

Common questions about Gemma 4 E4B vs GLM-5.3-Flash.

Which is better, Gemma 4 E4B or GLM-5.3-Flash?

GLM-5.3-Flash leads the LLM Stats Score 51.6 to 14.4. Gemma 4 E4B is made by Google and GLM-5.3-Flash 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 4 E4B compare to GLM-5.3-Flash in benchmarks?

Gemma 4 E4B scores MMMLU: 76.6%, MMLU-Pro: 69.4%, MathVision: 59.5%, GPQA: 58.6%, t2-bench: 57.5%. GLM-5.3-Flash scores CharXiv-R: 89.4%, Terminal-Bench 2.1: 84.3%, MMVU: 80.5%, Toolathlon: 78.4%, Chartography: 78.0%.

What are the context window sizes for Gemma 4 E4B and GLM-5.3-Flash?

Gemma 4 E4B supports an unknown number of tokens and GLM-5.3-Flash supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Gemma 4 E4B and GLM-5.3-Flash?

Key differences include LLM Stats Score (14.4 vs 51.6), licensing (Apache 2.0 vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemma 4 E4B and GLM-5.3-Flash?

Gemma 4 E4B is developed by Google and GLM-5.3-Flash is developed by Zhipu AI.

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