Head-to-Head Model Comparison

Grok-3 vs Claude 3.7 Sonnet

Benchmarks, API Token Pricing, Context Window & Speed Comparison

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

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Grok-3Profile

Claude 3.7 SonnetProfile

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xAI

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%

Anthropic

Claude 3.7 Sonnet

Líder em Programação e Código

O Claude 3.7 Sonnet da Anthropic é um modelo de IA projetado para engenharia de software autônoma, refatoração de código e depuração avançada, oferecendo janela de contexto de 200K, velocidade de 72 tokens/s, índice de inteligência de 48/10

Intelligence Index48 / 100

Input Token:

$3.00 / 1M

Output Token:

$15.00 / 1M

Context Window:

200K tokens

SWE-bench Verified:

70.3%

Principais Diferenças em Resumo

Claude 3.7 Sonnet is 1.0x cheaper for API usage (input + output tokens combined).
Grok-3 has a larger context window (1M vs 200K tokens).
Grok-3 is faster at 95 tok/s vs 72 tok/s.
Claude 3.7 Sonnet leads on SWE-bench coding (70.3% vs 65.2%).

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

Feature	Grok-3	Claude 3.7 Sonnet
Intelligence Index Composite reasoning & knowledge score (0-100)	54	48
Provider	xAI	Anthropic
Input Price Cost per million input tokens	$3.00 / 1M	$3.00 / 1M
Output Price Cost per million output tokens	$15.00 / 1M	$15.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$2.63 / 1M	$2.31 / 1M
Context Window Maximum input + output tokens	1M tokens~1,500 A4 pages of text	200K tokens~300 A4 pages of text
Max Output Tokens Per single request	33K	64K
Throughput Speed Tokens generated per second	95 tok/s	72 tok/s
SWE-bench Verified Real-world software engineering	65.2%	70.3%
GPQA Diamond Graduate-level reasoning	74%	65%
Cached Input Price Prompt caching discount per 1M tokens	$0.75 / 1M	$0.30 / 1M

Quem vence em cada categoria?

At-a-glance decision framework

Coding

Claude 3.7 Sonnet

+5.1% SWE-bench lead

Cost

Claude 3.7 Sonnet

1.0x cheaper monthly runtime

Speed

Grok-3

+32% faster generation

Context

Grok-3

1M tokens window

Pontuações de Benchmarks Verificadas

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

Grok-3Claude 3.7 Sonnet

SWE-bench Verified (Autonomous Coding)

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

65.2%vs70.3%

GPQA Diamond (Doctorate-Level Science & Math)

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

74%vs65%

MMLU-Pro (Multi-task Language Understanding)

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

88.5%vs78.2%

LMSYS Chatbot Arena Elo

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

1342ptsvs1335pts

Humanity's Last Exam (Frontier Expert Knowledge)

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

10.2%vs8.9%

Terminal-Bench (Agentic Coding & Terminal Use)

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

41%vs35.2%

SciCode (Scientific Computing)

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

42.5%vs40.1%

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

70.8%vs64.8%

AIME (Advanced Math Competition)

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

82.5%vs61.3%

Long-Context Reasoning

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

78.5%vs71.5%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

95 tok/s vs72 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

Claude 3.7 Sonnet0.52s

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

Grok-36.36s

Claude 3.7 Sonnet7.46s

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)

Grok-3 Monthly API Bill

$19.13 / month

$3/1M in · $15/1M out

Claude 3.7 Sonnet Monthly API Bill

$18.45 / month

$3/1M in · $15/1M out

Claude 3.7 Sonnet saves approximately $0.68 / month (4%) under this workload.1.0x 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

Claude 3.7 Sonnet · Strengths & Key Advantages

Janela de contexto de 200K com limite máximo de saída de 64K tokens (SWE-bench Verified 70.3% · GPQA Diamond 65%)
Taxa de transferência rápida de 72 tokens/segundo com latência inicial (TTFT) de 520 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

Token Use & Task Economics

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

Metric	Grok-3	Claude 3.7 Sonnet
Cost per Task Estimated USD to finish one task	$0.20	$1.42
Output Tokens / Task Tokens generated per task	24K	41K
Reasoning Tokens / Task Thinking tokens burned per task	15K	22K

Especificações Técnicas

Architecture, release timeline, capabilities, and modalities.

Feature	Grok-3	Claude 3.7 Sonnet
Official API Model ID (SDK)	grok-3-latest	claude-3-7-sonnet-20250201
API Protocol	xAI REST API (OpenAI-Compatible)	Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date	2025-02	2025-02
Knowledge Cutoff	Late 2024	November 2024
Architecture	Hybrid Reasoning Deep MoE	Hybrid Reasoning MoE
Parameters	Confidential	Confidential
Enterprise Rate Limits (RPM / TPM)	5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM	4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 800,000 – 2,000,000 TPM
Long-Context Tier (>128K/200K)	Flat rate ($3/1M in) across full 1000K window	Standard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTL	Cached input at $0.75/1M tokens	$0.3/1M cached read (90% off); 5-min default & 1-hour extended TTL
Computer Use / GUI Agent	API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)	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	Real-time Web & X (Twitter) Search Grounding + Code Execution	Native Web Search Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning Support	API Prompt Engineering & RAG Distillation	Custom Model Tuning via Amazon Bedrock & Prompt Distillation
Multimodal Token Billing	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)	Text BPE (~4 chars/token) · Vision (~258–765 tokens per image tile)
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	xAI Production Safety & Alignment Verified	Anthropic RSP ASL-2 / ASL-3 Constitutional Safety Evaluated
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	text, vision
Output Modalities	text	text

Grok-3 vs Claude 3.7 Sonnet: Respostas Rápidas (FAQ)

Which is more intelligent, Grok-3 or Claude 3.7 Sonnet?

Grok-3 is more intelligent. It scores 54 compared with 48 on the composite Intelligence Index.

Which model is faster?

Grok-3 is faster, generating 95 tokens per second compared with 72 tokens per second.

Which model is cheaper to run?

Claude 3.7 Sonnet is cheaper at $2.31 per 1M tokens blended, compared with $2.63 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Claude 3.7 Sonnet has lower latency, with a time to first token of 0.52s compared with 1.10s.

Which model has a larger context window?

Grok-3 has a larger context window, supporting 1M tokens compared with 200K 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 Claude 3.7 Sonnet (Indicado para engenharia de software autônoma, refatoração de código e depuração avançada, arquiteturas RAG corporativas e integração escalável via API.) entregam excelente desempenho: Grok-3 lidera em inteligência geral e programação, Grok-3 oferece geração mais rápida e Claude 3.7 Sonnet apresenta o melhor custo-benefício em produção.

Perguntas Frequentes (FAQ)

Qual é melhor para programação e raciocínio, Grok-3 ou Claude 3.7 Sonnet?+

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 Claude 3.7 Sonnet?+

O Grok-3 custa $3.00 / $15.00 por 1M de tokens (entrada/saída) e o Claude 3.7 Sonnet custa $3.00 / $15.00. No custo combinado, Claude 3.7 Sonnet é mais econômico.

Qual modelo possui maior janela de contexto e velocidade?+

O Grok-3 suporta 1M tokens de contexto contra 200K tokens do Claude 3.7 Sonnet, enquanto Grok-3 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)

Grok-3 vs Claude 3.7 Sonnet

Troque e Compare Qualquer Modelo

Grok-3

Claude 3.7 Sonnet

Quem vence em cada categoria?

Pontuações de Benchmarks Verificadas

Latência e Tempo de Resposta

Simulador Interativo de Custo de Tokens

Grok-3 · Strengths & Key Advantages

Considerations & Trade-offs

Claude 3.7 Sonnet · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Especificações Técnicas

Grok-3 vs Claude 3.7 Sonnet: Respostas Rápidas (FAQ)

Veredito

Perguntas Frequentes (FAQ)

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