Choosing between OpenAI's GPT-4o and Anthropic's Claude 3.5 Sonnet is one of the most
important decisions when implementing enterprise AI. It affects product quality, operating costs, and
the end-user experience.
This comparison is based on public benchmarks and real-world implementation experience
with clients across Guatemala, Mexico, and Colombia.
| Model | Context Window | Ideal use case |
|---|---|---|
| Claude 3.5 Sonnet | 200,000 tokens (~500 pages) | Case files, long contracts |
| GPT-4o | 128,000 tokens (~320 pages) | General tasks, code |
| Claude 3 Haiku | 200,000 tokens | Simple tasks, high volume |
Both models perform excellently in Spanish and other non-English languages, but with nuances:
| Model | Input (per 1M tokens) | Output (per 1M tokens) |
|---|---|---|
| Claude 3.5 Sonnet | $3.00 | $15.00 |
| GPT-4o | $5.00 | $15.00 |
| Claude 3 Haiku | $0.25 | $1.25 |
| GPT-4o mini | $0.15 | $0.60 |
Use GPT-4o when:
# API comparison: Claude vs GPT-4o
# --- Claude 3.5 (Anthropic SDK) ---
import anthropic
client = anthropic.Anthropic()
response = client.messages.create(
model="claude-sonnet-4-6",
max_tokens=2048,
system="You are a specialized legal analyst.",
messages=[{"role": "user", "content": prompt}]
)
text = response.content[0].text
# --- GPT-4o (OpenAI SDK) ---
from openai import OpenAI
client = OpenAI()
response = client.chat.completions.create(
model="gpt-4o",
messages=[
{"role": "system", "content": "You are a specialized legal analyst."},
{"role": "user", "content": prompt}
]
)
text = response.choices[0].message.contentCarlos Montiel is an enterprise AI solutions architect with experience in LLMs, Agents, RAG, and orchestration across Guatemala and Latin America.
Contact Carlos Montiel