Model Comparison
DeepSeek-V3 0324 vs Gemma 3 27BWhich is better in 2026?
DeepSeek-V3 0324 significantly outperforms across most benchmarks. Gemma 3 27B is 4.0x cheaper per token.
Verdict: DeepSeek-V3 0324 vs Gemma 3 27B — which is better?
DeepSeek-V3 0324 (by DeepSeek) and Gemma 3 27B (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 0324 outperforms in 3 benchmarks (GPQA, LiveCodeBench, MMLU-Pro), while Gemma 3 27B is better at 0 benchmarks. DeepSeek-V3 0324 significantly outperforms across most benchmarks.
On price, Gemma 3 27B is roughly 4.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V3 0324 also accepts a larger context window (163,840 input tokens), making it the stronger choice for long documents and large codebases.
Choose DeepSeek-V3 0324 if…
- you want the strongest raw capability — it leads on 3 of 3 shared benchmarks
- you process long inputs — it offers a 163,840 token context window
- you want the most recent training data — it shipped Mar 2025
Choose Gemma 3 27B if…
- cost matters — it's about 4.0x cheaper per token
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V3 0324 outperforms in 3 benchmarks (GPQA, LiveCodeBench, MMLU-Pro), while Gemma 3 27B is better at 0 benchmarks.
DeepSeek-V3 0324 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V3 0324 ($0.28/1M tokens) is 2.8x more expensive than Gemma 3 27B ($0.10/1M tokens).
For output processing, DeepSeek-V3 0324 ($1.14/1M tokens) is 5.7x more expensive than Gemma 3 27B ($0.20/1M tokens).
In conclusion, DeepSeek-V3 0324 is more expensive than Gemma 3 27B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V3 0324 has 644.0B more parameters than Gemma 3 27B, making it 2385.2% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V3 0324 accepts 163,840 input tokens compared to Gemma 3 27B's 131,072 tokens. DeepSeek-V3 0324 can generate longer responses up to 163,840 tokens, while Gemma 3 27B is limited to 131,072 tokens.
Input Capabilities
Supported data types and modalities
Gemma 3 27B supports multimodal inputs, whereas DeepSeek-V3 0324 does not.
Gemma 3 27B can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V3 0324
Gemma 3 27B
License
Usage and distribution terms
DeepSeek-V3 0324 is licensed under MIT + Model License (Commercial use allowed), while Gemma 3 27B uses Gemma.
License differences may affect how you can use these models in commercial or open-source projects.
MIT + Model License (Commercial use allowed)
Open weights
Gemma
Open weights
Release Timeline
When each model was launched
DeepSeek-V3 0324 was released on 2025-03-25, while Gemma 3 27B was released on 2025-03-12.
DeepSeek-V3 0324 is 0 month newer than Gemma 3 27B.
Mar 25, 2025
1.3 years ago
1w newerMar 12, 2025
1.3 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V3 0324 is available from Novita. Gemma 3 27B is available from DeepInfra, Novita.
DeepSeek-V3 0324
Gemma 3 27B
Outputs Comparison
Key Takeaways
DeepSeek-V3 0324
View detailsDeepSeek
Gemma 3 27B
View detailsDetailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against DeepSeek-V3 0324 and Gemma 3 27B side-by-side, then vote on the output you prefer.
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FAQ
Common questions about DeepSeek-V3 0324 vs Gemma 3 27B.