Model Comparison
DeepSeek-V3.2-Exp vs Gemma 3 4BWhich is better in 2026?
DeepSeek-V3.2-Exp significantly outperforms across most benchmarks. Gemma 3 4B is 12.2x cheaper per token.
Verdict: DeepSeek-V3.2-Exp vs Gemma 3 4B — which is better?
DeepSeek-V3.2-Exp (by DeepSeek) and Gemma 3 4B (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.
DeepSeek-V3.2-Exp outperforms in 4 benchmarks (GPQA, LiveCodeBench, MMLU-Pro, SimpleQA), while Gemma 3 4B is better at 0 benchmarks. DeepSeek-V3.2-Exp significantly outperforms across most benchmarks.
On price, Gemma 3 4B is roughly 12.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V3.2-Exp also accepts a larger context window (163,840 input tokens), making it the stronger choice for long documents and large codebases.
Choose DeepSeek-V3.2-Exp if…
- you want the strongest raw capability — it leads on 4 of 4 shared benchmarks
- you process long inputs — it offers a 163,840 token context window
- you want the most recent training data — it shipped Sep 2025
Choose Gemma 3 4B if…
- cost matters — it's about 12.2x cheaper per token
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V3.2-Exp outperforms in 4 benchmarks (GPQA, LiveCodeBench, MMLU-Pro, SimpleQA), while Gemma 3 4B is better at 0 benchmarks.
DeepSeek-V3.2-Exp significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V3.2-Exp ($0.27/1M tokens) is 13.5x more expensive than Gemma 3 4B ($0.02/1M tokens).
For output processing, DeepSeek-V3.2-Exp ($0.41/1M tokens) is 10.3x more expensive than Gemma 3 4B ($0.04/1M tokens).
In conclusion, DeepSeek-V3.2-Exp is more expensive than Gemma 3 4B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V3.2-Exp has 681.0B more parameters than Gemma 3 4B, making it 17025.0% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V3.2-Exp accepts 163,840 input tokens compared to Gemma 3 4B's 131,072 tokens. Gemma 3 4B can generate longer responses up to 131,072 tokens, while DeepSeek-V3.2-Exp is limited to 65,536 tokens.
Input Capabilities
Supported data types and modalities
Gemma 3 4B supports multimodal inputs, whereas DeepSeek-V3.2-Exp does not.
Gemma 3 4B can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V3.2-Exp
Gemma 3 4B
License
Usage and distribution terms
DeepSeek-V3.2-Exp is licensed under MIT, while Gemma 3 4B uses Gemma.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Gemma
Open weights
Release Timeline
When each model was launched
DeepSeek-V3.2-Exp was released on 2025-09-29, while Gemma 3 4B was released on 2025-03-12.
DeepSeek-V3.2-Exp is 7 months newer than Gemma 3 4B.
Sep 29, 2025
8 months ago
6mo newerMar 12, 2025
1.2 years ago
Knowledge Cutoff
When training data ends
Gemma 3 4B has a documented knowledge cutoff of 2024-08-01, while DeepSeek-V3.2-Exp'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 DeepSeek-V3.2-Exp's cutoff date.
—
Aug 2024
Provider Availability
DeepSeek-V3.2-Exp is available from Novita. Gemma 3 4B is available from DeepInfra.
DeepSeek-V3.2-Exp
Gemma 3 4B
Outputs Comparison
Key Takeaways
DeepSeek-V3.2-Exp
View detailsDeepSeek
Gemma 3 4B
View detailsDetailed Comparison
| Feature | | |
|---|
FAQ
Common questions about DeepSeek-V3.2-Exp vs Gemma 3 4B.