Gemma 2 9b Alternatives

google/gemma-2-9b-it is the instruction-tuned 9 billion parameter version of Google's Gemma 2 model. It uses a Gemma-specific chat template and is designed for conversational and instruction-following tasks. The model is fully open and can be run locally using Transformers, with support for various quantization formats and inference backends.

Gemma 2 2B is Google's open-weight language model with 2 billion parameters. It offers strong performance on reasoning, coding, and general language tasks while being small enough to run on consumer hardware or with limited cloud resources. The model is part of the Gemma 2 family and is fully open for research and commercial use.

Gemma 2B is Google's lightweight open-weight language model designed for text generation and research use cases. Released in 2024, it offers strong performance relative to its size and is available with both base and instruction-tuned variants. The model can be run locally or via cloud inference providers through the Hugging Face ecosystem.

Gemma-2-27B-IT is Google's 27-billion parameter instruction-tuned version of the Gemma 2 open model series. It excels at following instructions, reasoning, and generating coherent text. The model is distributed on Hugging Face and can be run locally or fine-tuned for specialized applications.

Gemma 2 2b It is an instruction-tuned language model published on Hugging Face by Google. It forms part of the Gemma 2 family of foundation models and is hosted for download and use through the Hugging Face platform. The model includes a specific chat template that structures conversations by alternating user and model roles. It applies special tokens such as start_of_turn, end_of_turn, eos, pad, and unk to format input and output. The template explicitly rejects a system role and enforces strict alternation between user and assistant messages. These elements support consistent dialogue formatting when the model is loaded with compatible libraries. The repository records over 10 million all-time downloads and more than 520,000 recent downloads. It was created on 2024-07-16. The page provides the model's configuration details alongside the chat template for integration into text-generation pipelines. As a foundation model hosted on Hugging Face, it is delivered as a downloadable repository containing model weights and associated tokenizer configuration. No pricing, licensing terms, or intended user roles beyond general availability on the platform are stated in the repository metadata.

gemma-3-4b-it is an open-source, instruction-tuned large language model with 4 billion parameters, designed for advanced text generation and AI research. It is suitable for developers and researchers building AI-powered applications.

Gemma 1.1 2B IT is Google's open-weights instruction-tuned language model designed for efficient text generation and conversational tasks. The 2-billion-parameter model includes a chat template and can be run locally via Transformers or other inference engines. It is targeted at developers who need a capable yet lightweight LLM that can be self-hosted or integrated into applications.

Gemma 3 1b It is an instruction-tuned language model hosted on Hugging Face. It belongs to the class of foundation models and provides a chat template for formatting conversational exchanges between user and model roles. The model includes a specific chat template that begins with a bos_token and handles optional system messages by extracting text content or using the first element of a content array. It enforces alternating user and assistant roles in conversations and raises an exception for any deviation from this pattern. Messages are formatted with start-of-turn tags that map the assistant role to "model" while preserving user and system roles, followed by trimmed content. The template supports both string and iterable content structures for messages. It is delivered as a model repository on the Hugging Face platform, where users can access the associated files and configuration for deployment in text generation and conversational applications. The surrounding platform offers access to models, datasets, and inference tools. The repository is maintained under the google organization on Hugging Face. No pricing, licensing terms, or additional capabilities are stated in the provided page content.

Gemma-4-E2B is a large open model from Google designed for any-to-any multimodal tasks including image-text-to-text. It is distributed on Hugging Face with full Transformers compatibility. The model targets developers building advanced multimodal applications.

gemma-3-1b-pt is the 1-billion parameter pre-trained (pt) base model from Google's Gemma 3 series. It is distributed openly on Hugging Face and is suitable for further fine-tuning or direct use in text-generation tasks. Its small size makes it ideal for resource-constrained environments.

Gemma 4 26B A4B it is a large open-source language model developed by Google for text generation, chat, and conversational AI. It supports fine-tuning and can be deployed locally or via API for a variety of NLP tasks. The model is suitable for machine learning engineers building advanced AI applications.

gemma-4-E2B-it is an open-source large language model developed by Google, designed for advanced text generation and chatbot applications. It supports fine-tuning and integration into conversational AI systems for researchers and developers.

Gemma-2-2B-IT is an instruction-tuned version of Google's Gemma 2 2 billion parameter model. It is optimized for following instructions and conversational use cases. The model can be run locally and is popular for on-device or privacy-sensitive applications where larger models are impractical.

Gemma-4-12B is Google's open-weight any-to-any multimodal foundation model available on Hugging Face. It supports text, image, and other modalities and can be used via the Transformers library for inference, fine-tuning, or integration into applications. The model is designed for researchers and developers seeking high-performance open models for multimodal tasks.

The 9 billion parameter instruction-tuned (IT) version of Google's Gemma 2 model, optimized by Unsloth for faster training and inference. It includes a custom chat template and is distributed in formats suitable for Hugging Face and local runtimes. Popular for both inference and continued fine-tuning.

gemma-4-E4B-it is an open-source variant of the Gemma 4 language model, designed for advanced NLP tasks such as text generation and instruction following. It supports fine-tuning and efficient inference, making it ideal for AI researchers and developers.

gemma-4-E4B is Google's open multimodal model capable of any-to-any tasks involving text and images. Released in 2026, it supports image-text-to-text pipelines and runs locally via the Transformers library. The model is provided as open weights on Hugging Face for researchers and developers exploring unified multimodal AI capabilities.

Gemma 4 31B IT is an open-source large language model developed by Google for text generation and conversational AI. It can be integrated via CLI or API and is suitable for research, experimentation, and building AI-powered applications.

google/gemma-4-31B-it-qat-w4a16-ct is a quantized, instruction-tuned large language model released by Google for research and development purposes. It supports text generation, multi-turn chat, and can be deployed locally or via API. The model is open source and suitable for AI researchers and developers seeking a high-performance LLM for experimentation or integration.

Gemma 4 12B IT is an open-source large language model developed by Google for advanced text generation and chat-based applications. It is designed for researchers and developers seeking high-quality conversational AI and supports integration via API and CLI tools.

gemma-2-2b-it-GGUF provides multiple quantized versions (IQ, Q3, Q4, Q5, Q6, Q8, f32) of Google's Gemma 2 2B instruction-tuned model in GGUF format. Created by bartowski, these files enable efficient local inference on CPUs and GPUs using tools like llama.cpp. The repository includes 11 different quantization options for various performance and accuracy tradeoffs.

This is a GGUF quantized version of Google's Gemma-4-E2B instruction-tuned model hosted on Hugging Face. It enables efficient local inference of a capable language model on consumer hardware using tools like llama.cpp or Ollama. The model supports text generation tasks and is popular among developers seeking open-weight models that can run without cloud dependency.

This is a quantized version of Google's Gemma 4 26B instruction-tuned (it) large language model. Hosted on Hugging Face, it provides open weights for developers to run locally or deploy on their own infrastructure. The model supports advanced features such as tool calling and follows a specific chat template, making it suitable for building AI applications, coding assistants, and conversational agents.

This Hugging Face repository hosts a Google Gemma 3n-E2B instruction-tuned model. It is intended for use with the Transformers library and includes a custom chat template. Like other Gemma releases, it is designed for text generation and can be run locally or via inference providers.

This is an optimized version of Google's Gemma 3 4B instruction-tuned (it) model hosted by Unsloth. It includes a specialized chat template for multi-turn conversations and is designed for efficient local inference. The model is suitable for on-device or self-hosted applications where smaller model size is preferred.

This repository hosts an AWQ (Activation-aware Weight Quantization) INT4 quantized variant of Google's Gemma-2-9B-IT model. It enables efficient local inference of a capable 9-billion-parameter instruction-tuned LLM on hardware with limited VRAM. The model is distributed via Hugging Face and is compatible with transformers and vLLM inference backends.

Gemma 2 9B IT is a web application that allows users to enter prompts and receive text responses generated by the Gemma-2 9B language model. It offers customization options for response style and length, serving both researchers and general users.

Gemma 4 12B It Qat W4a16 Ct is a quantized instruction-tuned language model hosted on Hugging Face. The model belongs to the Gemma 4 family and uses a specific quantization configuration indicated by its name, w4a16 with ct, along with a provided chat template for structured interactions. Its page supplies tokenizer configuration that defines special tokens including bos_token, eos_token, mask_token, pad_token, and unk_token. A chat_template_jinja is included with a macro for formatting parameters that handles properties such as description, type, and enum values for tool-calling and conversation formatting. The template notes updates for fixed tool-calling loops, turn closures, and thinking content-ordering, and is attributed to the Google Gemma Engineering Team with a listed publication date. The model is delivered as a repository on the Hugging Face platform, where users can access the model files, tokenizer, and associated configuration for local or hosted inference. It forms one implementation within the class of foundation models focused on text-based generation and instruction following.