LLMs & Models

GPT-4 vs Claude 3.5: Technical Comparison for Businesses 2026

By Carlos Montiel | Enterprise AI Solutions Architect | guatemalia.com
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✍️ Carlos Montiel 📂 LLMs & Models ⌛ 12 min read
In-depth analysis of GPT-4o vs Claude 3.5 Sonnet: context window, pricing, performance in non-English languages, and which model to choose for your enterprise use case.

The decision that most affects your project

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.

Context window: how much they can process

ModelContext WindowIdeal use case
Claude 3.5 Sonnet200,000 tokens (~500 pages)Case files, long contracts
GPT-4o128,000 tokens (~320 pages)General tasks, code
Claude 3 Haiku200,000 tokensSimple tasks, high volume
For analyzing complete medical case files (50+ pages) or lengthy contracts, Claude has a clear edge.

Performance in non-English languages

Both models perform excellently in Spanish and other non-English languages, but with nuances:

For corporate documents, contracts, or formal communications, Claude tends to be more precise.

Price comparison (June 2026)

ModelInput (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
At high volume (>10M tokens/month), the price difference on input tokens can add up significantly.

When to use each one?

Use GPT-4o when:

Use Claude 3.5 when:

Code example

# 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.content

Need to implement this at your company?

Carlos Montiel is an enterprise AI solutions architect with experience in LLMs, Agents, RAG, and orchestration across Guatemala and Latin America.

Contact Carlos Montiel
Carlos Montiel
Enterprise AI Solutions Architect · guatemalia.com

Specialist in LLMs, AI Agents, RAG, LangChain, and LangGraph for companies in Guatemala and Latin America. For implementation inquiries: guatemalia.com/en/#contact