QuantTrio/gemma-4-31B-it-AWQ
image-text-to-text model by QuantTrio
From the publisher
Model card & documentation
Source previewRead the publisher’s intended use, setup instructions, evaluations and limitations. The original model card is the source of truth.
Base model: google/gemma-4-31B-it This repo quantizes the model using data-free quantization (no calibration dataset required). As of 2026-04-03, make sure your system has cuda12.8 installed. Then, create a fresh Python environment (e.g. python3.12 venv) and run: Gemma4 vLLM Official Guide 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. 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 four distinct sizes: E2B, E4B, 26B A4B, and 31B. Their diverse sizes make them deployable in environments ranging from high-end phones to laptops and servers,…
Read the full model card ↗ · Preview checked 2026-10-30T07:03:25.698Z
Inside the original model card — Document outline
- gemma-4-31B-it-AWQ
- 【Dependencies / Installation】
- 【vLLM Startup Command】
- 【Logs】
- 【Model Files】
- 【Model Download】
- 【Overview】
- Models Overview
- Dense Models
- Mixture-of-Experts (MoE) Model
- Benchmark Results
- Core Capabilities
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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
QuantTrio/gemma-4-31B-it-AWQ is a image-text-to-text model repository published by QuantTrio 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)
- 665,151
- Cumulative likes
- 14
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 31,273,088,876
- Architecture
- Gemma4ForConditionalGeneration
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2026-04-03T23:59:34.000Z
- Last modified
- 2026-07-23T01:42:54.000Z
Compatibility and lineage
Language coverage was not reported.
Reported base models: google/gemma-4-31B-it
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.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-11-01T06:51:30.840Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.