Model Comparison
DeepSeek-V4-Pro-Max vs Gemma 4 31BWhich is better in 2026?
DeepSeek-V4-Pro-Max significantly outperforms across most benchmarks. Gemma 4 31B is 10.4x cheaper per token.
Verdict: DeepSeek-V4-Pro-Max vs Gemma 4 31B — which is better?
DeepSeek-V4-Pro-Max (by DeepSeek) and Gemma 4 31B (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-V4-Pro-Max outperforms in 4 benchmarks (GDPval-AA, GPQA, Humanity's Last Exam, MMLU-Pro), while Gemma 4 31B is better at 0 benchmarks. DeepSeek-V4-Pro-Max significantly outperforms across most benchmarks.
On price, Gemma 4 31B is roughly 10.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4-Pro-Max also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Choose DeepSeek-V4-Pro-Max if…
- you want the strongest raw capability — it leads on 4 of 4 shared benchmarks
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Apr 2026
Choose Gemma 4 31B if…
- cost matters — it's about 10.4x cheaper per token
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V4-Pro-Max outperforms in 4 benchmarks (GDPval-AA, GPQA, Humanity's Last Exam, MMLU-Pro), while Gemma 4 31B is better at 0 benchmarks.
DeepSeek-V4-Pro-Max significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Pro-Max ($1.60/1M tokens) is 12.3x more expensive than Gemma 4 31B ($0.13/1M tokens).
For output processing, DeepSeek-V4-Pro-Max ($3.20/1M tokens) is 8.4x more expensive than Gemma 4 31B ($0.38/1M tokens).
In conclusion, DeepSeek-V4-Pro-Max is more expensive than Gemma 4 31B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V4-Pro-Max has 1569.3B more parameters than Gemma 4 31B, making it 5111.7% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4-Pro-Max accepts 1,048,576 input tokens compared to Gemma 4 31B's 262,144 tokens. Both models can generate responses up to 131,072 tokens.
Input Capabilities
Supported data types and modalities
Gemma 4 31B supports multimodal inputs, whereas DeepSeek-V4-Pro-Max does not.
Gemma 4 31B can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4-Pro-Max
Gemma 4 31B
License
Usage and distribution terms
DeepSeek-V4-Pro-Max is licensed under MIT, while Gemma 4 31B uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
DeepSeek-V4-Pro-Max was released on 2026-04-23, while Gemma 4 31B was released on 2026-04-02.
DeepSeek-V4-Pro-Max is 1 month newer than Gemma 4 31B.
Apr 23, 2026
2 months ago
3w newerApr 2, 2026
3 months ago
Knowledge Cutoff
When training data ends
Gemma 4 31B has a documented knowledge cutoff of 2025-01-01, while DeepSeek-V4-Pro-Max's cutoff date is not specified.
We can confirm Gemma 4 31B's training data extends to 2025-01-01, but cannot make a direct comparison without DeepSeek-V4-Pro-Max's cutoff date.
—
Jan 2025
Provider Availability
DeepSeek-V4-Pro-Max is available from Novita, DeepInfra, DeepSeek, Fireworks, Together. Gemma 4 31B is available from DeepInfra, FriendliAI, Novita, Together.
DeepSeek-V4-Pro-Max
Gemma 4 31B
Outputs Comparison
Key Takeaways
DeepSeek-V4-Pro-Max
View detailsDeepSeek
Gemma 4 31B
View detailsDetailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek-V4-Pro-Max and Gemma 4 31B side-by-side, then vote on the output you prefer.
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FAQ
Common questions about DeepSeek-V4-Pro-Max vs Gemma 4 31B.