# 128k long context

KernelLLM is a model fine-tuned based on Llama 3.1 Instruct, specifically designed for writing GPU kernels using Triton.

xGen-small is an enterprise-grade compact language model that achieves long-context performance with predictable low costs through domain-focused data curation, scalable pre-training, length extension, and reinforcement learning fine-tuning.

A multimodal large model launched by Tongyi Qianwen, supporting image and text generation and 128k long context processing, with multilingual capabilities.

xLAM-2 is a series of large action models developed by Salesforce, focusing on multi-turn dialogue and function calling capabilities, serving as the core component of AI agents.

Llama 3.1 is a multilingual large language model series developed by Meta, including 8B, 70B, and 405B scales, supporting multilingual text generation and code generation tasks.

A 12-billion-parameter large language model optimized for speed, efficiency, and contextual accuracy, supporting RAG-enhanced technology and a 128k context window.

xLAM-2 is Salesforce's next-generation large action model, focusing on multi-turn dialogue and function calling capabilities, capable of translating user intent into executable actions, serving as the core component of AI agents.

The xLAM-2 series is a large-scale action model trained on the APIGen-MT framework, focusing on multi-round conversations and function calling capabilities, suitable for AI agent development.

xLAM-2 is a Large Action Model (LAM) series developed by SalesforceAIResearch, focusing on transforming user intent into executable actions to enhance AI agent decision-making capabilities.

Based on the Google Gemma-3 model, fine-tuned through 9 Neo and horror Imatrix methods, focusing on the generation of horror and fictional content

SEA-LION is a series of large language models pre-trained and instruction fine-tuned for the Southeast Asian region, dedicated to solving multilingual processing problems in this region and providing strong support for natural language processing of Southeast Asian languages.

Llama 3.2 is a collection of multilingual large language models launched by Meta, including pre-trained and instruction-tuned generative models of 1B and 3B sizes. It is optimized for multilingual dialogue use cases and performs well in common industry benchmark tests.

Llama 3.2 is a multilingual large language model series developed by Meta, including 1B and 3B scale pre-trained and instruction-tuned generative models, optimized for multilingual conversation scenarios.

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

Omost's phi-3-mini model with 128k context length, utilizing fp8 precision.

Yarn Mistral 7B 128K is an advanced language model optimized for long-context processing, further pre-trained on long-context data using the YaRN extension method, supporting a 128k token context window.