Head-to-Head Model Comparison

GPT-4o vs Gemini 1.5 Pro

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado pela equipe de pesquisa do GetInfoUsÚltima revisão: October 2026Política editorial

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GPT-4oProfile

Gemini 1.5 ProProfile

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OpenAI

GPT-4o

Modelo Nativo de Voz e Áudio

O GPT-4o da OpenAI é um modelo de IA projetado para síntese de voz natural, transcrição de áudio e interação falada em tempo real, oferecendo janela de contexto de 128K, velocidade de 105 tokens/s, índice de inteligência de 41/100 e tarifa

Intelligence Index41 / 100

Input Token:

$2.50 / 1M

Output Token:

$10.00 / 1M

Context Window:

128K tokens

SWE-bench Verified:

38.8%

Google

Gemini 1.5 Pro

Modelo de Geração Clássica

O Gemini 1.5 Pro da Google é um modelo de IA projetado para assistentes conversacionais, síntese de textos e tarefas corporativas, oferecendo janela de contexto de 2M, velocidade de 65 tokens/s, índice de inteligência de 46/100 e tarifa de

Intelligence Index46 / 100

Input Token:

$1.25 / 1M

Output Token:

$5.00 / 1M

Context Window:

2M tokens

SWE-bench Verified:

32.5%

Principais Diferenças em Resumo

Gemini 1.5 Pro is 2.1x cheaper for API usage (input + output tokens combined).
Gemini 1.5 Pro has a larger context window (2M vs 128K tokens).
GPT-4o is faster at 105 tok/s vs 65 tok/s.
GPT-4o leads on SWE-bench coding (38.8% vs 32.5%).

Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →

Feature	GPT-4o	Gemini 1.5 Pro
Intelligence Index Composite reasoning & knowledge score (0-100)	41	46
Provider	OpenAI	Google
Input Price Cost per million input tokens	$2.50 / 1M	$1.25 / 1M
Output Price Cost per million output tokens	$10.00 / 1M	$5.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$2.38 / 1M	$0.97 / 1M
Context Window Maximum input + output tokens	128K tokens~192 A4 pages of text	2M tokens~3,000 A4 pages of text
Max Output Tokens Per single request	16K	8K
Throughput Speed Tokens generated per second	105 tok/s	65 tok/s
SWE-bench Verified Real-world software engineering	38.8%	32.5%
GPQA Diamond Graduate-level reasoning	53.6%	58.5%
Cached Input Price Prompt caching discount per 1M tokens	$1.25 / 1M	$0.31 / 1M

Quem vence em cada categoria?

At-a-glance decision framework

Coding

GPT-4o

+6.3% SWE-bench lead

Cost

Gemini 1.5 Pro

2.1x cheaper monthly runtime

Speed

GPT-4o

+62% faster generation

Context

Gemini 1.5 Pro

2M tokens window

Pontuações de Benchmarks Verificadas

Official evaluation metrics verified by independent third-party research labs.

GPT-4oGemini 1.5 Pro

SWE-bench Verified (Autonomous Coding)

Industry benchmark evaluating real-world GitHub issue resolution and multi-file debugging.

38.8%vs32.5%

GPQA Diamond (Doctorate-Level Science & Math)

Challenging questions created by domain experts to test complex PhD-level reasoning.

53.6%vs58.5%

MMLU-Pro (Multi-task Language Understanding)

Hardened reasoning and academic knowledge benchmark with reduced lucky-guess probability.

72.6%vs75.2%

LMSYS Chatbot Arena Elo

Crowdsourced human preference evaluation based on blind, head-to-head model battles.

1286ptsvs1290pts

Humanity's Last Exam (Frontier Expert Knowledge)

Extremely difficult, closed-ended questions spanning the frontier of human expert knowledge.

4.1%vsN/A

Terminal-Bench (Agentic Coding & Terminal Use)

Autonomous multi-step tasks executed inside a real command-line terminal environment.

18.5%vsN/A

SciCode (Scientific Computing)

Research-grade coding problems drawn from real scientific and numerical workloads.

27.3%vsN/A

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

43.9%vsN/A

AIME (Advanced Math Competition)

American Invitational Mathematics Examination — multi-step Olympiad-level reasoning.

29.7%vsN/A

Long-Context Reasoning

Accuracy when reasoning over very large inputs that fill the model context window.

58.2%vs89.2%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

105 tok/s vs65 tok/s

Latência e Tempo de Resposta

Time to first token (TTFT) and estimated end-to-end response time for a typical 500-token response.

Time to First Token (TTFT)Lower is better

GPT-4o0.41s

Gemini 1.5 Pro0.80s

Est. End-to-End Response (500 tokens)TTFT + generation time

GPT-4o5.17s

Gemini 1.5 Pro8.49s

Simulador Interativo de Custo de Tokens

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

Daily Input Tokens100K / day

10K500K1M

Daily Output Tokens30K / day

5K150K300K

Prompt Cache Hit Ratio50% cached

0% (Cold)50%90% (Warm)

GPT-4o Monthly API Bill

$14.63 / month

$2.5/1M in · $10/1M out

Gemini 1.5 Pro Monthly API Bill

$6.84 / month

$1.25/1M in · $5/1M out

Gemini 1.5 Pro saves approximately $7.79 / month (53%) under this workload.2.1x Savings

GPT-4o · Strengths & Key Advantages

Janela de contexto de 128K com limite máximo de saída de 16K tokens (SWE-bench Verified 38.8% · GPQA Diamond 53.6%)
Taxa de transferência rápida de 105 tokens/segundo com latência inicial (TTFT) de 410 ms
Economia de API competitiva ($2.5/$10 por 1M de tokens) com suporte a cache de prompts e saídas JSON estruturadas

Considerations & Trade-offs

Modelo proprietário em nuvem; não permite download dos pesos para execução local offline
Para alto volume de requisições, recomenda-se ativar o cache de prompts e a Batch API para reduzir custos

Gemini 1.5 Pro · Strengths & Key Advantages

Janela de contexto de 2M com limite máximo de saída de 8K tokens (SWE-bench Verified 32.5% · GPQA Diamond 58.5%)
Taxa de transferência rápida de 65 tokens/segundo com latência inicial (TTFT) de 800 ms
Economia de API competitiva ($1.25/$5 por 1M de tokens) com suporte a cache de prompts e saídas JSON estruturadas

Considerations & Trade-offs

Modelo proprietário em nuvem; não permite download dos pesos para execução local offline
Em derivações científicas extremas, modelos pesados dedicados exclusivamente ao raciocínio oferecem maior profundidade

Token Use & Task Economics

Estimated cost and token consumption to complete one representative agentic task.

Metric	GPT-4o	Gemini 1.5 Pro
Cost per Task Estimated USD to finish one task	$0.68	$0.20
Output Tokens / Task Tokens generated per task	24K	24K
Reasoning Tokens / Task Thinking tokens burned per task	0K	0K

Especificações Técnicas

Architecture, release timeline, capabilities, and modalities.

Feature	GPT-4o	Gemini 1.5 Pro
Official API Model ID (SDK)	gpt-4o	models/gemini-1-5-pro
API Protocol	OpenAI Responses API & Chat Completions v1	Google Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date	2024-05	2024-02
Knowledge Cutoff	October 2023	May 2024
Architecture	Omni-Multimodal Dense	Sparse Mixture-of-Experts (MoE) Multimodal
Parameters	Confidential	Confidential
Enterprise Rate Limits (RPM / TPM)	10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM	10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)	Flat rate ($2.5/1M in) across full 128K window	Standard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTL	Automatic prefix caching at $1.25/1M (no extra cache-write fee)	Implicit + Explicit Context Caching at $0.31/1M with configurable TTL
Computer Use / GUI Agent	Supported (Screen coordinate grounding, browser & desktop GUI action loops)	Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool Calling	Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema	Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & Sandbox	Native Web Search tool + Hosted Code Interpreter & File Search RAG	Built-in Google Search Grounding + Managed Python Code Execution Sandbox
Official Fine-Tuning Support	Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)	Vertex AI Supervised Adapter Tuning & Context Distillation
Multimodal Token Billing	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec)	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec) · Video (~258–300 tokens/sec)
Quantization & Min GPU VRAM	Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)	Cloud-Hosted Proprietary (FP8 / BF16 Tensor Core Cluster) · Zero Local VRAM Required (100% Serverless Cloud API)
Safety & Frontier Classification	OpenAI Preparedness Framework Audited & System Card Published	Google DeepMind Frontier Safety Framework Verified
Enterprise Compliance (ZDR/HIPAA/SOC2)	SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier	SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalities	text, vision, audio	text, vision, audio, video
Output Modalities	text, audio	text

GPT-4o vs Gemini 1.5 Pro: Respostas Rápidas (FAQ)

Which is more intelligent, GPT-4o or Gemini 1.5 Pro?

Gemini 1.5 Pro is more intelligent. It scores 46 compared with 41 on the composite Intelligence Index.

Which model is faster?

GPT-4o is faster, generating 105 tokens per second compared with 65 tokens per second.

Which model is cheaper to run?

Gemini 1.5 Pro is cheaper at $0.97 per 1M tokens blended, compared with $2.38 (7:2:1 cache:input:output ratio).

Which model has lower latency?

GPT-4o has lower latency, with a time to first token of 0.41s compared with 0.80s.

Which model has a larger context window?

Gemini 1.5 Pro has a larger context window, supporting 2M tokens compared with 128K tokens.

Veredito

Tanto GPT-4o (Indicado para síntese de voz natural, transcrição de áudio e interação falada em tempo real, arquiteturas RAG corporativas e integração escalável via API.) quanto Gemini 1.5 Pro (Indicado para assistentes conversacionais, síntese de textos e tarefas corporativas, arquiteturas RAG corporativas e integração escalável via API.) entregam excelente desempenho: Gemini 1.5 Pro lidera em inteligência geral e programação, GPT-4o oferece geração mais rápida e Gemini 1.5 Pro apresenta o melhor custo-benefício em produção.

Perguntas Frequentes (FAQ)

Qual é melhor para programação e raciocínio, GPT-4o ou Gemini 1.5 Pro?+

Nas avaliações de inteligência e código, Gemini 1.5 Pro leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.

Qual modelo tem a API mais barata, GPT-4o ou Gemini 1.5 Pro?+

O GPT-4o custa $2.50 / $10.00 por 1M de tokens (entrada/saída) e o Gemini 1.5 Pro custa $1.25 / $5.00. No custo combinado, Gemini 1.5 Pro é mais econômico.

Qual modelo possui maior janela de contexto e velocidade?+

O GPT-4o suporta 128K tokens de contexto contra 2M tokens do Gemini 1.5 Pro, enquanto GPT-4o entrega maior velocidade de geração.

AI Terminology & Guide

Explore Glossary →

Understand key metrics like context window, token pricing, reasoning mode, and SWE-bench scores in our comprehensive AI glossary.

Tokens & Pricing Context Window AI Benchmarks Reasoning Models Tool Calling Model Context Protocol (MCP)

GPT-4o vs Gemini 1.5 Pro

Troque e Compare Qualquer Modelo

GPT-4o

Gemini 1.5 Pro

Quem vence em cada categoria?

Pontuações de Benchmarks Verificadas

Latência e Tempo de Resposta

Simulador Interativo de Custo de Tokens

GPT-4o · Strengths & Key Advantages

Considerations & Trade-offs

Gemini 1.5 Pro · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Especificações Técnicas

GPT-4o vs Gemini 1.5 Pro: Respostas Rápidas (FAQ)

Veredito

Perguntas Frequentes (FAQ)

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