Llama - 2026 Pricing, Features, Reviews & Alternatives

Llama is a family of open-access large language models (LLMs) from Meta, hosted on Hugging Face, spanning text-only and multimodal architectures from 1B to 405B parameters. The collection includes pretrained and instruction-tuned variants across multiple model generations: Llama 4 (natively multimodal, mixture-of-experts architecture, text and image input/output), Llama 3.2 Vision (11B and 90B, image reasoning, visual question answering, document question answering, image-text retrieval), Llama 3.2 text (1B and 3B, on-device, multilingual), Llama 3.1 (8B to 405B, multilingual, long context window, tool use), and Code Llama (base, Python-specialist, and instruct variants). Safety tooling includes Llama Guard for input/output classification aligned to the MLCommons hazard taxonomy, Prompt Guard, and Code Shield. Models are distributed in both original Meta format and Hugging Face Transformers format, and are available for commercial use under a permissive community license.

Deployment options cover cloud-based inference via Hugging Face Inference Endpoints (with continuous batching, token streaming, and tensor parallelism), major cloud platforms including Google Cloud Vertex AI, Amazon SageMaker, Microsoft Azure AI Studio, and DELL Enterprise Hub, as well as self-hosted deployment via Hugging Face Transformers and the Text Generation Inference container. The 1B and 3B text models support on-device and edge deployment without cloud dependency. Fine-tuning is supported through TRL and PEFT, including QLoRA for consumer-grade GPU hardware. The target audience spans individual AI researchers and ML engineers through to enterprises operating large-scale generative AI systems across technology, research, enterprise software, and consumer application domains.