MODEL PROFILE

gemma-2-9b-it-AWQ-INT4

hugging-quants · gemma-2-9b-it-AWQ-INT4

> [!IMPORTANT] > This repository is a community-driven quantized version of the original model `google/gemma-2-9b-it` which is the BF16 half-precision official version released by Google. > [!WARNING] > This model has been quantized using `transformers` 4.45.0, meaning that the tokenizer available in this repository won't be compatible with lower versions. Same applies for e.g. Text Generation Inference (TGI) that only installs `transformers` 4.45.0 or higher starting in v2.3.1. Gemma is a family of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create the Gemini models. They are text-to-text, decoder-only large language models, available in English, with open weights for both pre-trained variants and instruction-tuned variants. Gemma models are well-suited for a variety of text generation tasks, including question answering, summarization, and reasoning. Their relatively small size makes it possible to deploy them in environments with limited resources such as a laptop, desktop or your own cloud infrastructure, democratizing access to state of the art AI models and helping foster innovation for everyone.

Text generationlicense:gemma
Context windowNot disclosed
Input → OutputText → Text
Model weightsNot verified
Profile updated2026/10/28 22:34:30
OVERVIEW

Model overview

> [!IMPORTANT] > This repository is a community-driven quantized version of the original model `google/gemma-2-9b-it` which is the BF16 half-precision official version released by Google. > [!WARNING] > This model has been quantized using `transformers` 4.45.0, meaning that the tokenizer available in this repository won't be compatible with lower versions. Same applies for e.g. Text Generation Inference (TGI) that only installs `transformers` 4.45.0 or higher starting in v2.3.1. Gemma is a family of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create the Gemini models. They are text-to-text, decoder-only large language models, available in English, with open weights for both pre-trained variants and instruction-tuned variants. Gemma models are well-suited for a variety of text generation tasks, including question answering, summarization, and reasoning. Their relatively small size makes it possible to deploy them in environments with limited resources such as a laptop, desktop or your own cloud infrastructure, democratizing access to state of the art AI models and helping foster innovation for everyone.

Key features

特点摘要待依据来源补齐,不凭模型名称推断能力。

Limitations & considerations

Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.

PRICING & COST

Source prices & cost analysis

Prices vary by channel, region and configuration. Channel quotes are listed independently and are not treated as a single official provider price.

Source / channelInputOutputBilling unitCollected at
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Estimate monthly base token costs

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Estimates exclude cache discounts, tiered pricing, multimodal surcharges, web search, taxes and additional reasoning output.

INDEPENDENT BENCHMARKS

Public benchmarks & run configuration

暂无已采集的可核验公开评分。模型未上榜不代表能力较低。

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Frequently asked questions

Do open weights permit free commercial use?

Not necessarily. Check the version license, commercial conditions and usage policies. Self-hosting incurs compute and maintenance costs.

Are these real-time billing prices?

These are timestamped source snapshots, not live billing prices. Check the channel for current versions, regions, discounts and billing methods.

Sources & traceability

许可证:gemma。模型介绍与第三方评测均以原来源的具体版本和方法为准。