Open-weight Model
In one line
An open-weight model is an LLM whose weights are publicly released so anyone can download and run it on their own infrastructure — Llama, Mistral and Qwen are the best-known examples.
Going deeper
An open-weight model is one where the weight files are published, so anyone can download and run it locally. Meta's Llama, Mistral, Alibaba's Qwen and DeepSeek all fall into this bucket — in contrast to closed models like GPT or Claude that you can only access through an API.
This matters for brands because more companies are now fine-tuning open-weight models on their own data. When that happens, how your brand is represented in the underlying training data has a direct impact on what those private deployments say about you.
Worth noting: 'open-weight' is not the same as 'fully open-source'. Most releases share weights but not the training data or full code, and licences sometimes restrict commercial use.
Related terms
LLM
A large language model (LLM) is a neural network trained on massive text corpora to understand and generate human language — the engine behind ChatGPT, Claude, Gemini and similar products.
LLMFine-tuning
Fine-tuning takes an already pretrained LLM and trains it further on a narrower dataset to specialise it for a domain, task or voice — the most common path for adapting an LLM to your own data.
LLMPretraining
Pretraining is the initial stage where an LLM is trained on huge amounts of text to learn general language capability — the step where the model absorbs most of its 'world knowledge'.
LLMGPT
GPT (Generative Pre-trained Transformer) is OpenAI's family of Transformer-based LLMs — the engine behind ChatGPT and the de-facto baseline of the current AI market.
LLMClaude
Claude is Anthropic's LLM family, known for safety alignment, long-context handling and strong tool use — widely adopted in enterprise and developer settings.