# Multilingual generation

Gemma 3 is a lightweight open model series launched by Google, built on Gemini technology, supporting multimodal input and text output.

GGUF quantized version based on Qwen3-30B-A3B Mixture of Experts model, extended to 128k context, optimized with NEO Imatrix quantization technology, supporting multilingual and multitask processing.

Qwen3-8B-FP8-dynamic is an optimized version of the Qwen3-8B model through FP8 quantization, significantly reducing GPU memory requirements and disk space usage while maintaining the original model's performance.

Qwen3 is the latest generation of the Qwen series with 600 million parameters, supporting 32k context length and covering 119 languages

GLM-Z1-9B-0414 is a bilingual text generation model supporting both Chinese and English, utilizing the GGUF format and suitable for various quantization levels, from BF16 to ultra-low-bit quantization (1-2 bits).

Gemma 3 is a lightweight, state-of-the-art multimodal open-source model launched by Google, capable of processing text and image inputs and generating text outputs.

Gemma is a lightweight open model series launched by Google, built on Gemini model technology. Gemma 3 is a multimodal model supporting text and image inputs with text outputs, featuring a 128K large context window and multilingual capabilities.

Gemma 3 is a lightweight and state-of-the-art open model family launched by Google, built on the same research and technology as the Gemini model. It supports multimodal input and text output.

Gemma is a lightweight, advanced open model series from Google, built using the technology behind the Gemini models. Gemma 3 is a multimodal model capable of processing both text and image inputs to generate text outputs.

Gemma 3 is a lightweight, state-of-the-art multimodal open-source model launched by Google. It can process text and image inputs and generate text outputs, suitable for various text generation and image understanding tasks.

Gemma 3 is a lightweight and advanced open model series launched by Google, built on the same research and technology as the Gemini model. This version is an instruction-tuned model with 27B parameters, using quantization-aware training (QAT) and compressed tensor technology.

Gemma 3 is Google's lightweight cutting-edge open model family, built on the same research and technology used to create Gemini models. This model is multimodal, capable of processing both text and image inputs to generate text outputs.

Gemma is a lightweight, cutting-edge open model series from Google, built on Gemini technology. The 12B version is a multimodal model supporting text and image input, featuring a 128K large context window and support for over 140 languages.

Gemma 3 is a lightweight open-source multimodal model launched by Google, built on Gemini technology, supporting text and image input and generating text output.

GaMS-9B-Instruct is a Slovenian large language model developed based on Google Gemma 2 series, supporting Slovenian, English, and some South Slavic languages.

EXAONE-Deep-32B is a 32B-parameter large language model supporting English and Korean, specifically designed for text generation tasks.

Gemma is a lightweight and cutting-edge open model family launched by Google, built on the same research and technology as the Gemini model. Gemma 3 is a multimodal model that can process text and image inputs and generate text outputs.

Gemma is a lightweight open-source multimodal model series launched by Google. It supports text and image inputs and generates text outputs. It has a 128K large context window and supports over 140 languages.

A 7.8B-parameter model featuring ultra-low-bit quantization (1-2 bits) using IQ-DynamicGate technology, supporting English and Korean text generation tasks.

An 11-billion parameter large language model trained with the innovative SuperBPE tokenizer, supporting superword unit recognition and subword tokenization capabilities.

Gemma 3 is a series of lightweight open models launched by Google, supporting multimodal input (text and images), with a 128K large context window, suitable for various tasks such as question answering and summarization.

Gemma is Google's lightweight cutting-edge open model series, built using the same research technology as Gemini. The 1B version is instruction-tuned, suitable for deployment in resource-constrained environments.

Condor-Opus-14B-Exp is a large language model based on the Qwen 2.5 14B modal architecture, focusing on enhanced reasoning capabilities, supporting multilingual and long-context processing.

Lucie-7B is a multilingual causal language model with 7 billion parameters jointly built by LINAGORA and OpenLLM-France. It is based on the Llama-3 architecture and pre-trained on 3 trillion tokens of multilingual data.

A Japanese-optimized model fine-tuned based on Meta AI's Llama 3.2, supporting multilingual text generation

A version fine-tuned from Microsoft/Phi-3.5-mini-instruct, optimized for Italian language performance—a small yet powerful language model

FP8 quantized version of Meta-Llama-3.1-70B, suitable for multilingual business and research applications, with both weights and activations quantized to FP8 format, reducing storage and memory requirements by approximately 50%.

FP8 quantized version of Meta-Llama-3.1-8B, suitable for multilingual business and research applications.

Mistral-Nemo-Base-2407 is a 12-billion-parameter generative text pre-training model jointly trained by Mistral AI and NVIDIA, outperforming models of similar or smaller scale.

C4AI Command - R is a research version of a high-performance generative model with 35 billion parameters, optimized for various use cases such as inference, summarization, and question-answering.

A large Japanese - enhanced language model built on Meta Llama 3, which improves Japanese processing capabilities through continuous pre - training and instruction fine - tuning.

Typhoon-8B is a Thai large language model with 8 billion parameters built on Llama3-8B, focusing on text generation tasks in Thai and English.

This is a machine translation model fine-tuned based on Meta's NLLB-200 model, specifically designed for bidirectional translation tasks between Wolof and French.

A Korean language model continuously pre-trained based on Llama-3-8B, using over 60GB of deduplicated publicly available text for training, supporting Korean and English text generation.

Irbis-7B is a Transformer-based language model specifically optimized for Kazakh language, significantly improving Kazakh language processing quality

Mambaoutai is a series of small Mamba checkpoints, trained on data covering French, English, and code, intended for community exploration.

PULI LlumiX 32K is a large language model based on LLaMA-2-7B-32K, continuously pre-trained on Hungarian and English datasets, supporting 32K context length.

Occiglot-7B-DE-EN-Instruct is a multilingual large language model supporting German and English, developed based on occiglot-7b-eu5 with instruction fine-tuning, containing 7 billion parameters.

Swallow-MX-8x7b-NVE-v0.1 is a Mixture of Experts model based on Mixtral-8x7B-Instruct-v0.1 with continued pretraining, primarily enhancing Japanese capabilities.

A Ukrainian text verbalization model fine-tuned based on mbart-large-50, specifically designed for speech synthesis system adaptation