Model Comparison

DeepSeek-R1-0528 vs Gemma 3 12B

DeepSeek-R1-0528 significantly outperforms across most benchmarks. Gemma 3 12B is 14.6x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

DeepSeek-R1-0528 outperforms in 4 benchmarks (GPQA, LiveCodeBench, MMLU-Pro, SimpleQA), while Gemma 3 12B is better at 0 benchmarks.

DeepSeek-R1-0528 significantly outperforms across most benchmarks.

Sun Apr 19 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Gemma 3 12B costs less

For input processing, DeepSeek-R1-0528 ($0.50/1M tokens) is 10.0x more expensive than Gemma 3 12B ($0.05/1M tokens).

For output processing, DeepSeek-R1-0528 ($2.15/1M tokens) is 21.5x more expensive than Gemma 3 12B ($0.10/1M tokens).

In conclusion, DeepSeek-R1-0528 is more expensive than Gemma 3 12B.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Sun Apr 19 2026 • llm-stats.com
DeepSeek
DeepSeek-R1-0528
Input tokens$0.50
Output tokens$2.15
Best providerDeepinfra
Google
Gemma 3 12B
Input tokens$0.05
Output tokens$0.10
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

659.0B diff

DeepSeek-R1-0528 has 659.0B more parameters than Gemma 3 12B, making it 5491.7% larger.

DeepSeek
DeepSeek-R1-0528
671.0Bparameters
Google
Gemma 3 12B
12.0Bparameters
671.0B
DeepSeek-R1-0528
12.0B
Gemma 3 12B

Context Window

Maximum input and output token capacity

Both models have the same input context window of 131,072 tokens. Both models can generate responses up to 131,072 tokens.

DeepSeek
DeepSeek-R1-0528
Input131,072 tokens
Output131,072 tokens
Google
Gemma 3 12B
Input131,072 tokens
Output131,072 tokens
Sun Apr 19 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemma 3 12B supports multimodal inputs, whereas DeepSeek-R1-0528 does not.

Gemma 3 12B can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-R1-0528

Text
Images
Audio
Video

Gemma 3 12B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-R1-0528 is licensed under MIT, while Gemma 3 12B uses Gemma.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek-R1-0528

MIT

Open weights

Gemma 3 12B

Gemma

Open weights

Release Timeline

When each model was launched

DeepSeek-R1-0528 was released on 2025-05-28, while Gemma 3 12B was released on 2025-03-12.

DeepSeek-R1-0528 is 3 months newer than Gemma 3 12B.

DeepSeek-R1-0528

May 28, 2025

10 months ago

2mo newer
Gemma 3 12B

Mar 12, 2025

1.1 years ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

DeepSeek-R1-0528 is available from DeepInfra, DeepSeek, Novita. Gemma 3 12B is available from DeepInfra.

DeepSeek-R1-0528

deepinfra logo
Deepinfra
Input Price:Input: $0.50/1MOutput Price:Output: $2.15/1M
deepseek logo
DeepSeek
Input Price:Input: $0.55/1MOutput Price:Output: $2.19/1M
novita logo
Novita
Input Price:Input: $0.70/1MOutput Price:Output: $2.50/1M

Gemma 3 12B

deepinfra logo
Deepinfra
Input Price:Input: $0.05/1MOutput Price:Output: $0.10/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek
Higher GPQA score (81.0% vs 40.9%)
Higher LiveCodeBench score (73.3% vs 24.6%)
Higher MMLU-Pro score (85.0% vs 60.6%)
Higher SimpleQA score (92.3% vs 6.3%)
Google
Supports multimodal inputs
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-R1-0528
Google
Gemma 3 12B

FAQ

Common questions about DeepSeek-R1-0528 vs Gemma 3 12B

DeepSeek-R1-0528 significantly outperforms across most benchmarks. DeepSeek-R1-0528 is made by DeepSeek and Gemma 3 12B is made by Google. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek-R1-0528 scores MMLU-Redux: 93.4%, SimpleQA: 92.3%, AIME 2024: 91.4%, AIME 2025: 87.5%, MMLU-Pro: 85.0%. Gemma 3 12B scores GSM8k: 94.4%, IFEval: 88.9%, DocVQA: 87.1%, BIG-Bench Hard: 85.7%, HumanEval: 85.4%.
Gemma 3 12B is 10.0x cheaper for input tokens. DeepSeek-R1-0528 costs $0.50/M input and $2.15/M output via deepinfra. Gemma 3 12B costs $0.05/M input and $0.10/M output via deepinfra.
DeepSeek-R1-0528 supports 131K tokens and Gemma 3 12B supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include input pricing ($0.50 vs $0.05/M), multimodal support (no vs yes), licensing (MIT vs Gemma). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-R1-0528 is developed by DeepSeek and Gemma 3 12B is developed by Google.