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LatestGoogle DeepMind4-E4B-it
Google DeepMindAny-to-Any

Google Releases 4B Multimodal Gemma 4 Assistant

The new 4-billion-parameter model is instruction-tuned for 'any-to-any' tasks, handling a flexible mix of data types.

Apr 23, 2026
NotableApache 2.0
Gemma 4 E4B-it Assistant

Google DeepMind has expanded its open-source offerings with the release of Gemma 4 E4B-it Assistant, a new model in the Gemma family. At 4 billion parameters, this model is designed for efficiency while packing a significant new capability: advanced multimodality.

The model's standout feature is its 'any-to-any' architecture. Unlike models limited to text-and-image pairs, Gemma 4 is built to handle a more flexible combination of inputs and outputs. This design opens up possibilities for more integrated and versatile AI applications that can reason across different types of information simultaneously.

As an instruction-tuned ('it') variant, Gemma 4 is optimized out-of-the-box for conversational AI and assistant-like interactions. This fine-tuning makes it easier for developers to build responsive and helpful applications without extensive additional training.

By releasing a capable and efficient multimodal model under a commercially permissive Apache 2.0 license, Google is providing developers with a key building block for the next wave of AI applications. Researchers and engineers can explore the model's capabilities and access the full release details on the Hugging Face Hub. This move brings functionality often associated with larger, closed systems to the open-source community, enabling broader experimentation and innovation.

Sources

  • google/gemma-4-E4B-it-assistant

    Hugging Face

    Visit
OlderGoogle Releases 2B Multimodal Gemma 4 Assistant ModelGoogle DeepMind · Any-to-Any · 6 months agoNewerGoogle Releases Multimodal Gemma 4 31B ModelGoogle DeepMind · Any-to-Any · 6 months ago

Get the model

Hugging Face

Specs

Parameters4B
Context window131K tokens
PrecisionBF16
ArchitectureGemma4AssistantForCausalLM
LicenseAPACHE-2.0
Downloads15.8K
Likes136

Can you run it?

Runs on just about anything.

  • BF16 (as published)

    12 GB GPU (RTX 3060 / 4070) · 16 GB Mac

    9.1 GB
  • 8-bit

    8 GB GPU (RTX 4060) · 16 GB laptop or Mac

    5.3 GB
  • 4-bit

    Any modern laptop · 8 GB RAM

    3.5 GB
Your machine
GGUF builds
  • Parameter count is an editorial estimate — no weights metadata on Hugging Face.
  • KV cache sized for 8,192 tokens of context; longer prompts need proportionally more.

Estimated from the parameter count. Assumes an 8K context and ~1 GB runtime overhead; actual needs vary. How we estimate


Modalities

Text / LLMAny-to-Any

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