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Chat

Chat models are conversational generalists.
In Particula they are used for:

  • interactive tutorials & “explain‑this‑output” prompts,
  • translating user intent to build small function or class calls.

Each chat request is wrapped in a vector‑RAG layer that pulls the most relevant Particula API & docs snippets before the prompt reaches the LLM.

graph TB
    U["User"] -->|prompt| REAS["Chat Model"]
    REAS -->|tool call| VS[(Vector Store)]
    VS --> |API/Examples/Theory| REAS
    REAS -->|final answer| U

GPT‑4o

GPT‑4o (o for omni) is a multimodal model that natively handles text, images, and (soon) audio & video inside one architecture.

  • 128 k‑token context
  • GPT‑4‑Turbo parity on code & English 
  • better vision & non‑English.

Use for: integrated visual or mixed‑media reasoning (diagrams, photos, future A/V).

GPT‑4.1

April 2025 upgrade to 4o.

  • 1 M‑token context window
  • +21 % coding accuracy vs 4o 
  • 26 % cheaper ops.

Use for: very‑long‑context refactors, legal/scientific deep‑dives, multi‑step agents.

GPT‑4.1mini & GPT‑4.1nano

  • mini – ½ latency, 83 % cheaper than 4o, still beats it on many tasks.
  • nano – smallest & fastest of 4.1.

Use for: mini → balanced power/cost; nano → ultra‑light, real‑time or mobile agents.

Reference: