Model Comparison
GLM-5 vs Gemma 3n E4B InstructedWhich is better in 2026?
Comparing GLM-5 and Gemma 3n E4B Instructed across benchmarks, pricing, and capabilities.
Verdict: GLM-5 vs Gemma 3n E4B Instructed — which is better?
GLM-5 (by Zhipu AI) and Gemma 3n E4B Instructed (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.
On price, GLM-5 is roughly 16.1x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GLM-5 also accepts a larger context window (200,000 input tokens), making it the stronger choice for long documents and large codebases.
Choose GLM-5 if…
- cost matters — it's about 16.1x cheaper per token
- you process long inputs — it offers a 200,000 token context window
- 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 Instructed if…
- you want predictable pricing at $20.00/M input and $40.00/M output
Performance Benchmarks
Comparative analysis across standard metrics
GLM-5 and Gemma 3n E4B Instructed don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-5 ($1.00/1M tokens) is 20.0x cheaper than Gemma 3n E4B Instructed ($20.00/1M tokens).
For output processing, GLM-5 ($3.20/1M tokens) is 12.5x cheaper than Gemma 3n E4B Instructed ($40.00/1M tokens).
In conclusion, Gemma 3n E4B Instructed is more expensive than GLM-5.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-5 has 736.0B more parameters than Gemma 3n E4B Instructed, making it 9200.0% larger.
Context Window
Maximum input and output token capacity
GLM-5 accepts 200,000 input tokens compared to Gemma 3n E4B Instructed's 32,000 tokens. GLM-5 can generate longer responses up to 128,000 tokens, while Gemma 3n E4B Instructed is limited to 32,000 tokens.
Input Capabilities
Supported data types and modalities
Gemma 3n E4B Instructed supports multimodal inputs, whereas GLM-5 does not.
Gemma 3n E4B Instructed can handle both text and other forms of data like images, making it suitable for multimodal applications.
GLM-5
Gemma 3n E4B Instructed
License
Usage and distribution terms
GLM-5 is licensed under MIT, while Gemma 3n E4B Instructed uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
GLM-5 was released on 2026-02-11, while Gemma 3n E4B Instructed was released on 2025-06-26.
GLM-5 is 8 months newer than Gemma 3n E4B Instructed.
Feb 11, 2026
3 months ago
7mo newerJun 26, 2025
11 months ago
Knowledge Cutoff
When training data ends
Gemma 3n E4B Instructed has a documented knowledge cutoff of 2024-06-01, while GLM-5's cutoff date is not specified.
We can confirm Gemma 3n E4B Instructed's training data extends to 2024-06-01, but cannot make a direct comparison without GLM-5's cutoff date.
—
Jun 2024
Provider Availability
GLM-5 is available from FriendliAI, ZAI. Gemma 3n E4B Instructed is available from Together.
GLM-5
Gemma 3n E4B Instructed
Outputs Comparison
Key Takeaways
GLM-5
View detailsZhipu AI
Detailed Comparison
| Feature | | |
|---|
FAQ
Common questions about GLM-5 vs Gemma 3n E4B Instructed.