Editing Openai/6939b23e-87cc-8001-bdd9-9546d1143ce9 (section)

=== Assistant: Yes — that’s a perfect observation, and it reveals how LLM inference works in practice. ===
Yes — that’s a perfect observation, and it reveals how LLM inference works in practice. Let me explain carefully what’s happening under the hood in LM Studio (or similar GUI tools).

==== - When you insert a big prompt, LM Studio first tokenizes it. - Converts your text into model-readable tokens. - Counts tokens to make sure they fit into the model’s context window. ====
* Then, depending on the GUI/tool, it might estimate progress: - Percentage might indicate tokenization + initial context preparation. - For large prompts, this step can take noticeable time because the software needs to encode all tokens into embeddings that the model will use.

: 

==== - After the prompt is processed, the model starts token-by-token generation: - Each token goes through all layers (attention + feed-forward + pattern recognition). - This is the “thinking” the GUI shows. - For larger models, each token takes longer because there are more layers, attention heads, and neurons to compute. ====
* If the output is long, you may see this phase last several seconds or minutes, because each token is processed sequentially.

==== - Tokens are appended to the context and passed forward in sequence. ====
* The GUI displays them as text in real time (or once generation finishes).
* From the model’s perspective, the entire prompt + all previously generated tokens is just one big context sequence.

: 

==== - Tokenization and embedding preparation can be fast, but token generation is sequential and dependent. ====
* The % progress you see is often a rough heuristic; real “thinking” speed varies with: - Model size - Prompt length - Token complexity (long words, rare terms) - Hardware (GPU/CPU, VRAM, batch optimization)

===== - Processing Prompt… X% → tokenization + context setup =====
* Thinking → sequential forward passes, token-by-token, through all layers
* Output → tokens appended to context, displayed as final result

: 

If you want, I can make a diagram showing LM Studio’s workflow: prompt → tokenization → token-by-token generation → output, to visualize what happens during “Processing…” and “Thinking.”

Do you want me to do that?