Large Language Models (LLMs) AI Tools

Open-weight LLM by Meta available in 8B, 70B, and 405B parameter sizes.

Latest Llama model family by Meta with Mixture-of-Experts architecture.

High-performance open-weight LLMs by Mistral AI with MoE architecture.

Open-weight LLM family by Alibaba with strong multilingual and coding abilities.

High-performance open-weight MoE LLM with 671B total parameters.

Reasoning-focused open-weight LLM with chain-of-thought capabilities.

Lightweight open-weight LLM by Google available in 1B to 27B sizes.

Small language model by Microsoft with strong reasoning for its size.

Retrieval-augmented generation optimized LLM by Cohere with 128K context.

Open-weight bilingual LLM by 01.AI in 6B and 34B sizes.

Open-weight LLM by Shanghai AI Lab with strong reasoning and tool use.

Open-weight bilingual LLM by Zhipu AI with multimodal capabilities.

Open-access 176B parameter multilingual LLM by BigScience supporting 46 languages.

Open-weight LLM by TII achieving top performance with efficient training.

Compact 1.1B parameter LLM pre-trained on 3 trillion tokens.

Family of small language models by Hugging Face for on-device use.

RNN-based language model with transformer-level performance and linear scaling.

State-space model for language with linear-time sequence modeling.

Fully open language model by AI2 with open data, code, and training logs.

Open-weight code LLM by BigCode trained on 600+ programming languages.

Code-specialized Llama model by Meta for code generation and understanding.

Open-weight code LLM trained on 2 trillion tokens of code and natural language.

Open-source code LLM family by IBM for enterprise code generation.

Compact edge-deployable LLM family by OpenBMB with strong performance per parameter.

Fine-tuned LLaMA model by LMSYS achieving 90% ChatGPT quality.

Hybrid SSM-Transformer model by AI21 Labs combining Mamba with attention layers.

Open-weight language model family by Stability AI for text generation.

Open-source LLM by MosaicML trained for commercial use with 65K context.

Open-source reproduction of LLaMA training dataset and models.

Fine-tuned Mistral 7B achieving top performance through curated training data.

LLM fine-tuned with Evol-Instruct for complex instruction following.

Multimodal and lightweight Llama models by Meta including vision and text-only variants.

Small language model by Microsoft in 3.8B size with strong benchmark performance.

Open-weight models by Google in 2B, 9B, and 27B sizes with strong performance.

Open-weight LLM by Meta in 8B and 70B sizes with strong general capabilities.

Multimodal vision-language model by Alibaba for image understanding.

Visual instruction tuned multimodal LLM for image understanding and chat.

Open-source multimodal LLM competitive with commercial models by Shanghai AI Lab.

Fine-tuned LLM series by Nous Research known for instruction following.

Multimodal vision-language model by Mistral AI for image understanding.