All blog posts, tools, and guides about Llama from Developers Digest.
7 resources - 2 posts, 4 tools, 1 guide

Meta's Llama 4 family brings mixture-of-experts to open source with Scout and Maverick. Here's how to run them locally, access them through APIs, and decide when they beat the competition.

Meta surprised the AI community with Llama 3.3, a 70 billion parameter model that delivers 405B-class performance at a fraction of the cost. Here is what the benchmarks show, where to run it, and why this release matters for developers building with open-source models.
LLM data framework for connecting custom data sources to language models. Best-in-class RAG, data connectors, and query engines. Python and TypeScript.
AI FrameworksMeta's open-source model family. Llama 4 available in Scout (17B active) and Maverick (17B active, 128 experts). Free to use, modify, and deploy commercially.
AI ModelsThe easiest way to run LLMs locally. One command to pull and run any model. OpenAI-compatible API. 52M+ monthly downloads. Supports GGUF, Safetensors, and custom Modelfiles.
Local AIC++ inference engine for LLMs. GGUF format, quantization, CPU and Metal/CUDA support. The foundation most local tools build on.
Local AI
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