Comprehensive side-by-side LLM comparison
Gemma 3 12B supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
DeepSeek
DeepSeek-V3.1, released by DeepSeek in August 2025, is a hybrid large language model with 671 billion total parameters (37 billion active) that unifies the capabilities of DeepSeek-V3 and DeepSeek-R1 in a single model. It features a 128K token context window and supports both direct generation and extended reasoning modes selectable via the chat template. DeepSeek-V3.1 targets general-purpose tasks, coding, and complex reasoning under an open MIT license.
Google DeepMind
Gemma 3 12B is a 12-billion-parameter open-weight model from Google DeepMind, released in March 2025 as part of the Gemma 3 series designed to bring multimodal reasoning to accessible hardware. The model supports both text and image inputs across a 128K token context window, extending the vision capabilities that defined the Gemma 3 generation compared to earlier text-only Gemma releases. It became widely adopted for domain-specific fine-tuning in research and enterprise settings where full multimodal capability was needed without the infrastructure demands of larger frontier models.
5 months newer

Gemma 3 12B
Google DeepMind
2025-03-12

DeepSeek-V3.1
DeepSeek
2025-08-21
Context window and performance specifications
Available providers and their performance metrics
DeepSeek-V3.1
DeepSeek
Gemma 3 12B
DeepSeek-V3.1
Gemma 3 12B
DeepSeek-V3.1
Gemma 3 12B