Model Comparison

DeepSeek-V3.2-Speciale vs Gemma 3 12B

Comparing DeepSeek-V3.2-Speciale and Gemma 3 12B across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V3.2-Speciale and Gemma 3 12B don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Gemma 3 12B costs less

For input processing, DeepSeek-V3.2-Speciale ($0.28/1M tokens) is 5.6x more expensive than Gemma 3 12B ($0.05/1M tokens).

For output processing, DeepSeek-V3.2-Speciale ($0.42/1M tokens) is 4.2x more expensive than Gemma 3 12B ($0.10/1M tokens).

In conclusion, DeepSeek-V3.2-Speciale is more expensive than Gemma 3 12B.*

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

Lowest available price from all providers
Wed Apr 22 2026 • llm-stats.com
DeepSeek
DeepSeek-V3.2-Speciale
Input tokens$0.28
Output tokens$0.42
Best providerDeepSeek
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

673.0B diff

DeepSeek-V3.2-Speciale has 673.0B more parameters than Gemma 3 12B, making it 5608.3% larger.

DeepSeek
DeepSeek-V3.2-Speciale
685.0Bparameters
Google
Gemma 3 12B
12.0Bparameters
685.0B
DeepSeek-V3.2-Speciale
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-V3.2-Speciale
Input131,072 tokens
Output131,072 tokens
Google
Gemma 3 12B
Input131,072 tokens
Output131,072 tokens
Wed Apr 22 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemma 3 12B supports multimodal inputs, whereas DeepSeek-V3.2-Speciale does not.

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

DeepSeek-V3.2-Speciale

Text
Images
Audio
Video

Gemma 3 12B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3.2-Speciale 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-V3.2-Speciale

MIT

Open weights

Gemma 3 12B

Gemma

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.2-Speciale was released on 2025-12-01, while Gemma 3 12B was released on 2025-03-12.

DeepSeek-V3.2-Speciale is 9 months newer than Gemma 3 12B.

DeepSeek-V3.2-Speciale

Dec 1, 2025

4 months ago

8mo 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-V3.2-Speciale is available from DeepSeek. Gemma 3 12B is available from DeepInfra.

DeepSeek-V3.2-Speciale

deepseek logo
DeepSeek
Input Price:Input: $0.28/1MOutput Price:Output: $0.42/1M

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

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Google
Supports multimodal inputs
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.2-Speciale
Google
Gemma 3 12B

FAQ

Common questions about DeepSeek-V3.2-Speciale vs Gemma 3 12B

DeepSeek-V3.2-Speciale (DeepSeek) and Gemma 3 12B (Google) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
DeepSeek-V3.2-Speciale scores HMMT 2025: 99.2%, AIME 2025: 96.0%, CodeForces: 90.0%, t2-bench: 80.3%, SWE-Bench Verified: 73.1%. 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 5.6x cheaper for input tokens. DeepSeek-V3.2-Speciale costs $0.28/M input and $0.42/M output via deepseek. Gemma 3 12B costs $0.05/M input and $0.10/M output via deepinfra.
DeepSeek-V3.2-Speciale 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 ($0.28 vs $0.05/M), multimodal support (no vs yes), licensing (MIT vs Gemma). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3.2-Speciale is developed by DeepSeek and Gemma 3 12B is developed by Google.