Yes — in about 90% of technical conversations, people use both expressions to mean the same thing.
But there’s an important nuance once you work as an AI Engineer.
Let me give you both the simple version and the precise professional version.
✅ Simple version (what most people mean)
👉 “Launching a model” = “Launching an LLM”
People use both to mean:
- loading the model into memory
- starting the inference engine
- getting the model ready to answer prompts
Examples:
- “I launched the Llama3:8B model.”
- “I launched the LLM locally with Ollama.”
→ Same meaning in everyday discussions.
🎯 Precise version (the one that matters for AI engineers)
There is actually a technical difference:
🔹 “Launching a model”
This is generic.
Not all models are LLMs.
A model could be:
- an image classifier
- a recommendation model
- a price prediction model
- an embedding model
- or an LLM
So “model” is the broad category.
🔹 “Launching an LLM”
This is specific:
It refers to launching a large language model, usually based on a transformer decoder architecture.
Examples:
- Llama 3
- GPT-4
- Mistral 7B
- Phi-3 Mini
- Qwen 2
All of these are models — but specifically LLMs.
🧠 Easy summary
- All LLMs are models.
- But not all models are LLMs.
Just like:
- “vehicle” (generic)
- “Tesla” (specific type of vehicle)
🛠️ In actual AI engineering practice:
If you’re talking about NLP / chatbots / RAG:
→ “launching a model” and “launching an LLM” = same thing in context.
If you’re talking about machine learning in general:
→ “model” is broader than “LLM”.