Model Comparison
DeepSeek-V2.5 vs Gemma 3 4BWhich is better in 2026?
DeepSeek-V2.5 shows notably better performance in the majority of benchmarks. Gemma 3 4B is 7.0x cheaper per token.
Verdict: DeepSeek-V2.5 vs Gemma 3 4B — which is better?
DeepSeek-V2.5 (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-V2.5 outperforms in 2 benchmarks (GSM8k, HumanEval), while Gemma 3 4B is better at 1 benchmark (MATH). DeepSeek-V2.5 shows notably better performance in the majority of benchmarks.
On price, Gemma 3 4B is roughly 7.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Gemma 3 4B also accepts a larger context window (131,072 input tokens), making it the stronger choice for long documents and large codebases.
Choose DeepSeek-V2.5 if…
- you want the strongest raw capability — it leads on 2 of 3 shared benchmarks
Choose Gemma 3 4B if…
- cost matters — it's about 7.0x cheaper per token
- you process long inputs — it offers a 131,072 token context window
- you want the most recent training data — it shipped Mar 2025
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V2.5 outperforms in 2 benchmarks (GSM8k, HumanEval), while Gemma 3 4B is better at 1 benchmark (MATH).
DeepSeek-V2.5 shows notably better performance in the majority of benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V2.5 ($0.14/1M tokens) is 7.0x more expensive than Gemma 3 4B ($0.02/1M tokens).
For output processing, DeepSeek-V2.5 ($0.28/1M tokens) is 7.0x more expensive than Gemma 3 4B ($0.04/1M tokens).
In conclusion, DeepSeek-V2.5 is more expensive than Gemma 3 4B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V2.5 has 232.0B more parameters than Gemma 3 4B, making it 5800.0% larger.
Context Window
Maximum input and output token capacity
Gemma 3 4B accepts 131,072 input tokens compared to DeepSeek-V2.5's 8,192 tokens. Gemma 3 4B can generate longer responses up to 131,072 tokens, while DeepSeek-V2.5 is limited to 8,192 tokens.
Input Capabilities
Supported data types and modalities
Gemma 3 4B supports multimodal inputs, whereas DeepSeek-V2.5 does not.
Gemma 3 4B can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V2.5
Gemma 3 4B
License
Usage and distribution terms
DeepSeek-V2.5 is licensed under deepseek, while Gemma 3 4B uses Gemma.
License differences may affect how you can use these models in commercial or open-source projects.
deepseek
Open weights
Gemma
Open weights
Release Timeline
When each model was launched
DeepSeek-V2.5 was released on 2024-05-08, while Gemma 3 4B was released on 2025-03-12.
Gemma 3 4B is 10 months newer than DeepSeek-V2.5.
May 8, 2024
2.2 years ago
Mar 12, 2025
1.4 years ago
10mo newerKnowledge Cutoff
When training data ends
Gemma 3 4B has a documented knowledge cutoff of 2024-08-01, while DeepSeek-V2.5'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 DeepSeek-V2.5's cutoff date.
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Aug 2024
Provider Availability
DeepSeek-V2.5 is available from DeepSeek, DeepInfra, Hyperbolic. Gemma 3 4B is available from DeepInfra.
DeepSeek-V2.5
Gemma 3 4B
Outputs Comparison
Key Takeaways
DeepSeek-V2.5
View detailsDeepSeek
Gemma 3 4B
View detailsDetailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek-V2.5 and Gemma 3 4B side-by-side, then vote on the output you prefer.
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FAQ
Common questions about DeepSeek-V2.5 vs Gemma 3 4B.