Compare AI Text Models (2025)

Selecting an LLM involves trade‑offs in quality, latency, cost, tools, and safety. This guide contrasts popular models and shows how to integrate them via a unified API.

At‑a‑glance

Feature comparison

Unified API examples

OpenAI Chat Completions — JavaScript

import axios from "axios";

const payload = {
  model: "gpt-4o-mini",
  messages: [
    { role: "system", content: "You are a concise assistant." },
    { role: "user", content: "Summarize the key benefits of a unified API layer." },
  ],
  temperature: 0.7,
};

const res = await axios.post(
  "https://api.coreapi.com/v1/openai/chat/completions",
  payload,
  { headers: { Authorization: `Bearer ${process.env.CORE_API_KEY}` } }
);
console.log(res.data);

Anthropic Messages — Python

import requests, os

payload = {
    "model": "claude-3-5-sonnet",
    "max_tokens": 512,
    "temperature": 0.7,
    "messages": [
        {"role": "user", "content": "List 5 common pitfalls in multi-vendor AI integrations."}
    ],
}

r = requests.post(
    "https://api.coreapi.com/v1/claude/messages",
    json=payload,
    headers={"Authorization": f"Bearer {os.environ['CORE_API_KEY']}"},
)
print(r.json())

Choosing a model

• Prefer GPT‑4o for robust tools/function‑calling and strong reasoning.
• Prefer Claude for extended context and helpful writing.
• Prefer Gemini for multimodal, long‑context document workflows.
• Prefer Llama when you need open weights and deployment control.