Head-to-Head Model Comparison

Grok-3 vs GPT-4o

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado pela equipe de pesquisa do GetInfoUsÚltima revisão: October 2026Política editorial
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Grok-3 vs GPT-4o: Benchmarks, Pricing & Speed Comparison

Grok-3 da xAI e GPT-4o da OpenAI são dois modelos de IA de destaque. O Grok-3 oferece uma janela de contexto de 1M tokens a $3.00/$15.00 por milhão de tokens, enquanto o GPT-4o oferece 128K tokens de contexto a $2.50/$10.00 por milhão de tokens. Veja abaixo a comparação completa de benchmarks, latência e custos.

Comparação Direta (VS)

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Grok-3

Motor de Raciocínio Profundo

O Grok-3 da xAI é um modelo de IA projetado para raciocínio lógico profundo, matemática avançada e análise científica passo a passo, oferecendo janela de contexto de 1M, velocidade de 95 tokens/s, índice de inteligência de 54/100 e tarifa d

Intelligence Index54 / 100
Input Token:

$3.00 / 1M

Output Token:

$15.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

65.2%

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%

Principais Diferenças em Resumo

  • GPT-4o is 1.3x cheaper for API usage (input + output tokens combined).
  • Grok-3 has a larger context window (1M vs 128K tokens).
  • GPT-4o is faster at 105 tok/s vs 95 tok/s.
  • Grok-3 leads on SWE-bench coding (65.2% vs 38.8%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGrok-3GPT-4o
Intelligence Index
Composite reasoning & knowledge score (0-100)
5441
Provider
xAIOpenAI
Input Price
Cost per million input tokens
$3.00 / 1M$2.50 / 1M
Output Price
Cost per million output tokens
$15.00 / 1M$10.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$2.63 / 1M$2.38 / 1M
Context Window
Maximum input + output tokens
1M tokens~1,500 A4 pages of text128K tokens~192 A4 pages of text
Max Output Tokens
Per single request
33K16K
Throughput Speed
Tokens generated per second
95 tok/s105 tok/s
SWE-bench Verified
Real-world software engineering
65.2%38.8%
GPQA Diamond
Graduate-level reasoning
74%53.6%
Cached Input Price
Prompt caching discount per 1M tokens
$0.75 / 1M$1.25 / 1M

Quem vence em cada categoria?

At-a-glance decision framework
Coding
Grok-3
+26.4% SWE-bench lead
Cost
GPT-4o
1.3x cheaper monthly runtime
Speed
GPT-4o
+11% faster generation
Context
Grok-3
1M tokens window

Pontuações de Benchmarks Verificadas

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

Grok-3GPT-4o
SWE-bench Verified (Autonomous Coding)

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

65.2%vs38.8%
GPQA Diamond (Doctorate-Level Science & Math)

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

74%vs53.6%
MMLU-Pro (Multi-task Language Understanding)

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

88.5%vs72.6%
LMSYS Chatbot Arena Elo

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

1342ptsvs1286pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

10.2%vs4.1%
Terminal-Bench (Agentic Coding & Terminal Use)

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

41%vs18.5%
SciCode (Scientific Computing)

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

42.5%vs27.3%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

70.8%vs43.9%
AIME (Advanced Math Competition)

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

82.5%vs29.7%
Long-Context Reasoning

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

78.5%vs58.2%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

95 tok/s vs105 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
Grok-31.10s
GPT-4o0.41s
Est. End-to-End Response (500 tokens)TTFT + generation time
Grok-36.36s
GPT-4o5.17s

Simulador Interativo de Custo de Tokens

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

100K / day
10K500K1M
30K / day
5K150K300K
50% cached
0% (Cold)50%90% (Warm)
Grok-3 Monthly API Bill
$19.13 / month
$3/1M in · $15/1M out
GPT-4o Monthly API Bill
$14.63 / month
$2.5/1M in · $10/1M out
GPT-4o saves approximately $4.50 / month (24%) under this workload.1.3x Savings

Grok-3 · Strengths & Key Advantages

  • Janela de contexto de 1M com limite máximo de saída de 33K tokens (SWE-bench Verified 65.2% · GPQA Diamond 74%)
  • Taxa de transferência rápida de 95 tokens/segundo com latência inicial (TTFT) de 1100 ms
  • Economia de API competitiva ($3/$15 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

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

Token Use & Task Economics

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

MetricGrok-3GPT-4o
Cost per Task
Estimated USD to finish one task
$0.20$0.68
Output Tokens / Task
Tokens generated per task
24K24K
Reasoning Tokens / Task
Thinking tokens burned per task
15K0K

Especificações Técnicas

Architecture, release timeline, capabilities, and modalities.

FeatureGrok-3GPT-4o
Official API Model ID (SDK)grok-3-latestgpt-4o
API ProtocolxAI REST API (OpenAI-Compatible)OpenAI Responses API & Chat Completions v1
Release Date2025-022024-05
Knowledge CutoffLate 2024October 2023
ArchitectureHybrid Reasoning Deep MoEOmni-Multimodal Dense
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM10,000 – 30,000 RPM (Tier 5 Enterprise) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($3/1M in) across full 1000K windowFlat rate ($2.5/1M in) across full 128K window
Prompt Cache Policy & TTLCached input at $0.75/1M tokensAutomatic prefix caching at $1.25/1M (no extra cache-write fee)
Computer Use / GUI AgentAPI / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool CallingNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON SchemaNative MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & SandboxReal-time Web & X (Twitter) Search Grounding + Code ExecutionNative Web Search tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning SupportAPI Prompt Engineering & RAG DistillationSupervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
Multimodal Token BillingText BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile) · Audio (~25–32 tokens/sec)
Quantization & Min GPU VRAMCloud-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 ClassificationxAI Production Safety & Alignment VerifiedOpenAI Preparedness Framework Audited & System Card Published
Enterprise Compliance (ZDR/HIPAA/SOC2)SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, visiontext, vision, audio
Output Modalitiestexttext, audio

Grok-3 vs GPT-4o: Respostas Rápidas (FAQ)

Which is more intelligent, Grok-3 or GPT-4o?

Grok-3 is more intelligent. It scores 54 compared with 41 on the composite Intelligence Index.

Which model is faster?

GPT-4o is faster, generating 105 tokens per second compared with 95 tokens per second.

Which model is cheaper to run?

GPT-4o is cheaper at $2.38 per 1M tokens blended, compared with $2.63 (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 1.10s.

Which model has a larger context window?

Grok-3 has a larger context window, supporting 1M tokens compared with 128K tokens.

Veredito

Tanto Grok-3 (Indicado para raciocínio lógico profundo, matemática avançada e análise científica passo a passo, arquiteturas RAG corporativas e integração escalável via API.) quanto 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.) entregam excelente desempenho: Grok-3 lidera em inteligência geral e programação, GPT-4o oferece geração mais rápida e GPT-4o apresenta o melhor custo-benefício em produção.

Perguntas Frequentes (FAQ)

Qual é melhor para programação e raciocínio, Grok-3 ou GPT-4o?+

Nas avaliações de inteligência e código, Grok-3 leva vantagem. Confira os gráficos SWE-bench e GPQA acima para detalhes.

Qual modelo tem a API mais barata, Grok-3 ou GPT-4o?+

O Grok-3 custa $3.00 / $15.00 por 1M de tokens (entrada/saída) e o GPT-4o custa $2.50 / $10.00. No custo combinado, GPT-4o é mais econômico.

Qual modelo possui maior janela de contexto e velocidade?+

O Grok-3 suporta 1M tokens de contexto contra 128K tokens do GPT-4o, 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.

Benchmark scores, token prices, and rate limits evolve rapidly as AI labs release model updates. Always verify current specifications and pricing on the official provider documentation.

Fontes oficiais: Documentação oficial de API da xAI e OpenAI e benchmarks independentes (2026).