DeepSeek-V4-Pro-0813 vs Gemma 3 4B
Comparing DeepSeek-V4-Pro-0813 and Gemma 3 4B across benchmarks, pricing, and capabilities.
DeepSeek · Google · Updated for 2026
Which is better?
DeepSeek-V4-Pro-0813 and Gemma 3 4B trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, Gemma 3 4B is roughly 21.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4-Pro-0813 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 DeepSeek-V4-Pro-0813
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Aug 2026
Choose Gemma 3 4B
- cost matters — it's about 21.7x cheaper per token
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V4-Pro-0813 and Gemma 3 4Bdon'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, DeepSeek-V4-Pro-0813 ($0.43/1M tokens) is 21.8x more expensive than Gemma 3 4B ($0.02/1M tokens).
For output processing, DeepSeek-V4-Pro-0813 ($0.87/1M tokens) is 21.8x more expensive than Gemma 3 4B ($0.04/1M tokens).
In conclusion, DeepSeek-V4-Pro-0813 is more expensive than Gemma 3 4B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4-Pro-0813 has 1596.0B more parameters than Gemma 3 4B, making it 39900.0% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4-Pro-0813 accepts 1,048,576 input tokens compared to Gemma 3 4B's 131,072 tokens. DeepSeek-V4-Pro-0813 can generate longer responses up to 393,216 tokens, while Gemma 3 4B is limited to 131,072 tokens.
Input Capabilities
Supported data types and modalities
Gemma 3 4B supports multimodal inputs, whereas DeepSeek-V4-Pro-0813 does not.
Gemma 3 4B can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4-Pro-0813
Gemma 3 4B
License
Usage and distribution terms
DeepSeek-V4-Pro-0813 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-V4-Pro-0813 was released on 2026-08-13, while Gemma 3 4B was released on 2025-03-12.
DeepSeek-V4-Pro-0813 is 17 months newer than Gemma 3 4B.
Aug 13, 2026
1 weeks ago
1.4yr newerMar 12, 2025
1.5 years ago
Knowledge Cutoff
When training data ends
Gemma 3 4B has a documented knowledge cutoff of 2024-08-01, while DeepSeek-V4-Pro-0813'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-V4-Pro-0813's cutoff date.
—
Aug 2024
Provider Availability
DeepSeek-V4-Pro-0813 is available from DeepSeek, DeepInfra, Novita, Together. Gemma 3 4B is available from DeepInfra.
DeepSeek-V4-Pro-0813
Gemma 3 4B
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Pro-0813 and Gemma 3 4B side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Pro-0813 vs Gemma 3 4B.