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Gemma 3 12B vs MiniMax M2.1
Comprehensive side-by-side LLM comparison
Gemma 3 12B supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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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.
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MiniMax
MiniMax M2.1, released by MiniMax on December 23, 2025, is a large language model with approximately 230 billion parameters featuring strong multi-language programming capabilities and an industry-leading multilingual coding profile. It features a 196K token context window and is optimized for complex real-world software engineering tasks across Rust, Java, Golang, C++, TypeScript, and other languages. M2.1 targets agentic coding workflows and applications requiring production-grade programming across diverse language environments.
9 months newer
Gemma 3 12B
Google DeepMind
2025-03-12
MiniMax M2.1
MiniMax
2025-12-23
Performance Metrics
Context window and performance specifications
Provider Availability & Performance
Available providers and their performance metrics
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Gemma 3 12B
0 providers
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MiniMax M2.1
1 providers
MiniMax
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Gemma 3 12B
Avg Score:0.0%
Providers:0
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MiniMax M2.1
Avg Score:0.0%
Providers:1