Gemma 2 2b It Alternatives

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 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-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.

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 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 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 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-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-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-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.

Gemma 2 9b is a 9-billion-parameter language model hosted on Hugging Face. It belongs to the class of foundation models and supports the text-generation task. The model was created by Google and released on the platform in June 2024. It has accumulated over 1.9 million downloads and maintains an active inference status. The repository provides tokenizer configuration that defines special tokens including a beginning-of-sequence token, end-of-sequence token, padding token, and unknown token. Its use_default_system_prompt setting is disabled. Gemma 2 9b can be accessed through multiple inference providers. One listed provider is featherless-ai, where the model runs with live status for text-generation workloads. The model files are stored in safetensors format. It is available for direct use on the Hugging Face site and through the platform's ecosystem of tools for models, datasets, and spaces. The entry appears in a catalog that emphasizes open source and open science. No pricing, license text, or explicit target audience is stated on the page.

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.

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.

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.

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 is an instruction-tuned ('it-assistant') version of Google's Gemma 4 model series. It is designed for conversational and assistant-style tasks and is distributed on Hugging Face for use with the Transformers library. The model supports local inference and further customization.

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.

Gemma 2 2B IT is a web-based interface for interacting with a large language model, allowing users to input messages or questions and receive AI-generated natural-language responses. It supports prompt customization and adjustable response settings, making it suitable for general users interested in exploring conversational AI.

gemma-4-12B-it-assistant is Google's latest open-weights instruction-tuned language model with 12 billion parameters. It is designed for high-quality assistant-style interactions and text generation. The model is hosted on Hugging Face, uses the Transformers library, and is suitable for research and commercial applications.

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 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-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-4-12B 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.

This is an Unsloth-optimized version of Google's Gemma-4 12B instruction-tuned (it) model. It includes a specialized chat template and is designed for efficient fine-tuning and inference. The model is made available on Hugging Face for developers and researchers working with open large language models.

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.

This is a 4-bit quantized GGUF version of Google's Gemma-4 2B (E2B) instruction-tuned model. The QAT (Quantization Aware Training) and GGUF format allow efficient local inference using tools like llama.cpp. It is designed for on-device or local LLM applications.

unsloth/gemma-3-27b-it provides optimized weights and tools for fine-tuning Google's Gemma 3 27B instruction-tuned model using the Unsloth library. It offers faster training and lower memory usage compared to standard approaches while maintaining full model performance. The model is designed for developers who want to customize large language models for specific tasks.

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.

This is an instruction-tuned version of Google's Gemma-4 4B model designed for assistant-style interactions. It supports advanced prompting, tool use, and multi-turn dialogue. The model is openly available on Hugging Face for local or self-hosted deployment.

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.