Gemma is a family of open models built by Google DeepMind. Gemma 4 models are multimodal, handling text and image input (with audio supported on small models) and generating text output.

Gemma 4 introduces key capability and architectural advancements:

Custom Fields

Special features defined by the model author

Enable Thinking

: boolean

(default=true)

Controls whether the model will think before replying

Parameters

Custom configuration options included with this model

Reasoning Section Parsing

{ "enabled": true, "startString": "<|channel>thought", "endString": "<channel|>" }

Temperature

Top K Sampling

Top P Sampling

Sources

The underlying model files this model uses

0.95

Reasoning – All models in the family are designed as highly capable reasoners, with configurable thinking modes.

Extended Multimodalities – Processes Text, Image with variable aspect ratio and resolution support.

Diverse & Efficient Architectures – Offers Dense and Mixture-of-Experts (MoE) variants of different sizes for scalable deployment.

Optimized for On-Device – Smaller models are specifically designed for efficient local execution on laptops and mobile devices.

Increased Context Window – The small models feature a 128K context window, while the medium models support 256K.

Enhanced Coding & Agentic Capabilities – Achieves notable improvements in coding benchmarks alongside native function-calling support, powering highly capable autonomous agents.

Native System Prompt Support – Gemma 4 introduces native support for the system role, enabling more structured and controllable conversations.

Based on

🤗lmstudio-community/gemma-4-E2B-it-GGUF→

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