Gemma 3n E4B Instructed vs GLM-5.3-Flash
Comparing Gemma 3n E4B Instructed and GLM-5.3-Flash across benchmarks, pricing, and capabilities.
Google · Zhipu AI · Updated for 2026
Which is better?
Gemma 3n E4B Instructed and GLM-5.3-Flash trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, GLM-5.3-Flash is roughly 105.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GLM-5.3-Flash also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Based on current benchmark, pricing, and model metadata for 2026.
Choose Gemma 3n E4B Instructed
- you want predictable pricing at $20.00/M input and $40.00/M output
Choose GLM-5.3-Flash
- cost matters — it's about 105.3x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Aug 2026
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
Gemma 3n E4B Instructed and GLM-5.3-Flashdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Gemma 3n E4B Instructed ($20.00/1M tokens) is 133.3x more expensive than GLM-5.3-Flash ($0.15/1M tokens).
For output processing, Gemma 3n E4B Instructed ($40.00/1M tokens) is 80.0x more expensive than GLM-5.3-Flash ($0.50/1M tokens).
In conclusion, Gemma 3n E4B Instructed is more expensive than GLM-5.3-Flash.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-5.3-Flash has 312.0B more parameters than Gemma 3n E4B Instructed, making it 3900.0% larger.
Context Window
Maximum input and output token capacity
GLM-5.3-Flash accepts 1,048,576 input tokens compared to Gemma 3n E4B Instructed's 32,000 tokens. GLM-5.3-Flash can generate longer responses up to 131,072 tokens, while Gemma 3n E4B Instructed is limited to 32,000 tokens.
Input Capabilities
Supported data types and modalities
Both Gemma 3n E4B Instructed and GLM-5.3-Flash support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Gemma 3n E4B Instructed
GLM-5.3-Flash
License
Usage and distribution terms
Gemma 3n E4B Instructed is licensed under a proprietary license, while GLM-5.3-Flash uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
MIT
Open weights
Release Timeline
When each model was launched
Gemma 3n E4B Instructed was released on 2025-06-26, while GLM-5.3-Flash was released on 2026-08-26.
GLM-5.3-Flash is 14 months newer than Gemma 3n E4B Instructed.
Jun 26, 2025
1.2 years ago
Aug 26, 2026
0 days ago
1.2yr newerKnowledge Cutoff
When training data ends
Gemma 3n E4B Instructed has a documented knowledge cutoff of 2024-06-01, while GLM-5.3-Flash'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-5.3-Flash's cutoff date.
Jun 2024
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Provider Availability
Gemma 3n E4B Instructed is available from Together. GLM-5.3-Flash is available from DeepInfra, Novita, ZAI.
Gemma 3n E4B Instructed
GLM-5.3-Flash
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemma 3n E4B Instructed and GLM-5.3-Flash side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemma 3n E4B Instructed vs GLM-5.3-Flash.