Gemma 3 4B vs GLM-4.5
GLM-4.5 leads the LLM Stats Score 28.0 to -1.7. Gemma 3 4B is 28.0x cheaper per token.
Google · Zhipu AI · Updated for 2026
Which is better?
GLM-4.5 leads the overall LLM Stats Score 28.0 to -1.7, ranking #128 overall.
In the 3 individual benchmarks reported for both models, GLM-4.5 wins 3; this is a narrower head-to-head signal than the composite indexes.
On price, Gemma 3 4B is roughly 28.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Gemma 3 4B
- cost matters — it's about 28.0x cheaper per token
Choose GLM-4.5
- overall performance matters — it scores 28.0 and ranks #128 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 3 of 3 exact shared results
- you want the most recent training data — it shipped Jul 2025
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
26 reported for Gemma 3 4B · 14 for GLM-4.5
Gemma 3 4B outperforms in 0 benchmarks, while GLM-4.5 is better at 3 benchmarks (GPQA, LiveCodeBench, MMLU-Pro).
GLM-4.5 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Gemma 3 4B ($0.02/1M tokens) is 20.0x cheaper than GLM-4.5 ($0.40/1M tokens).
For output processing, Gemma 3 4B ($0.04/1M tokens) is 40.0x cheaper than GLM-4.5 ($1.60/1M tokens).
In conclusion, GLM-4.5 is more expensive than Gemma 3 4B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-4.5 has 351.0B more parameters than Gemma 3 4B, making it 8775.0% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 131,072 tokens. Both models can generate responses up to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Gemma 3 4B supports multimodal inputs, whereas GLM-4.5 does not.
Gemma 3 4B can handle both text and other forms of data like images, making it suitable for multimodal applications.
Gemma 3 4B
GLM-4.5
License
Usage and distribution terms
Gemma 3 4B is licensed under Gemma, while GLM-4.5 uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Gemma
Open weights
MIT
Open weights
Release Timeline
When each model was launched
Gemma 3 4B was released on 2025-03-12, while GLM-4.5 was released on 2025-07-28.
GLM-4.5 is 5 months newer than Gemma 3 4B.
Mar 12, 2025
1.5 years ago
Jul 28, 2025
1.1 years ago
4mo newerKnowledge Cutoff
When training data ends
Gemma 3 4B has a documented knowledge cutoff of 2024-08-01, while GLM-4.5's cutoff date is not specified.
We can confirm Gemma 3 4B's training data extends to 2024-08-01, but cannot make a direct comparison without GLM-4.5's cutoff date.
Aug 2024
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Provider Availability
Gemma 3 4B is available from DeepInfra. GLM-4.5 is available from DeepInfra, Fireworks, Novita.
Gemma 3 4B
GLM-4.5
Outputs Comparison
Judge for yourself.
Run your own prompts against Gemma 3 4B and GLM-4.5 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Gemma 3 4B vs GLM-4.5.