google/gemma-4-26B-A4B-it

image-text-to-text model by google

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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 E2B, E4B, and 12B) and generating text output. This release includes open-weights models in both pre-trained and instruction-tuned variants. Gemma 4 features a context window of up to 256K tokens and maintains multilingual support in over 140 languages. Featuring both Dense and Mixture-of-Experts (MoE) architectures, Gemma 4 is well-suited for tasks like text generation, coding, and reasoning. The models are available in five distinct sizes: E2B, E4B, 12B, 26B A4B, and 31B. Their diverse sizes make them deployable in environments ranging from high-end phones to laptops and servers, democratizing access to state-of-the-art AI. Gemma 4 introduces key capability and architectural advancements: Gemma 4 models are designed to deliver frontier-level performance at each size, targeting deployment scenarios from mobile and edge devices (E2B, E4B) to consumer…

google/gemma-4-26B-A4B-it on Hugging Face A short preview, not the full document.

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Inside the original model card — Document outline
  1. Models Overview
  2. Dense Models
  3. Mixture-of-Experts (MoE) Model
  4. Benchmark Results
  5. Core Capabilities
  6. Getting Started
  7. Best Practices
  8. 1. Sampling Parameters
  9. 2. Thinking Mode Configuration
  10. 3. Multi-Turn Conversations
  11. 4. Modality order
  12. 5. Variable Image Resolution

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Documentation belongs to its respective authors. Reported project/model license: apache-2.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.

Model overview

google/gemma-4-26B-A4B-it is a image-text-to-text model repository published by google on Hugging Face. The source reports the transformers library.

This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.

Model facts

Task
image-text-to-text
Library
transformers
Recent downloads (30 days)
6,135,897
Cumulative likes
1,724
Hugging Face trending score
19
Reported safetensors parameters
25,805,936,206
Architecture
Gemma4ForConditionalGeneration
License
apache-2.0
Access
Not gated by Hugging Face
Created
2026-03-11T21:25:57.000Z
Last modified
2026-07-20T16:42:12.000Z

Compatibility and lineage

Language coverage was not reported.

Reported base models: google/gemma-4-26B-A4B

Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.

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Source: Hugging Face Hub. Metadata observed 2026-11-01T06:51:30.840Z. Daily imports are snapshots, not real-time monitoring.

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