Head-to-Head Model Comparison

Grok 4.7 vs GPT-6 Sol

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado por el equipo de investigación de GetInfoUsÚltima revisión: October 2026Política editorial

Cambia y Compara Cualquier Modelo

Select any AI models from our verified benchmark database to generate live side-by-side matrices.

Grok 4.7Profile

GPT-6 SolProfile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

xAI

Grok 4.7

Modelo Insignia de Frontera

Grok 4.7 de xAI es un modelo de IA diseñado para razonamiento empresarial de frontera, programación avanzada y flujos de producción, con ventana de contexto de 500K, velocidad de 110 tokens/s, índice de inteligencia de 46/100 y tarifa de $2

Intelligence Index46 / 100

Input Token:

$2.00 / 1M

Output Token:

$6.00 / 1M

Context Window:

500K tokens

SWE-bench Verified:

77.2%

OpenAI

GPT-6 Sol

Modelo Insignia de Frontera

GPT-6 Sol de OpenAI es un modelo de IA diseñado para razonamiento empresarial de frontera, programación avanzada y flujos de producción, con ventana de contexto de 1M, velocidad de 116 tokens/s, índice de inteligencia de 93/100 y tarifa de

Intelligence Index93 / 100

Input Token:

$2.00 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

82.1%

Diferencias Clave de un Vistazo

Grok 4.7 is 1.3x cheaper for API usage (input + output tokens combined).
GPT-6 Sol has a larger context window (1M vs 500K tokens).
GPT-6 Sol is faster at 116 tok/s vs 110 tok/s.
GPT-6 Sol leads on SWE-bench coding (82.1% vs 77.2%).

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

Característica	Grok 4.7	GPT-6 Sol
Intelligence Index Composite reasoning & knowledge score (0-100)	46	93
Provider	xAI	OpenAI
Input Price Cost per million input tokens	$2.00 / 1M	$2.00 / 1M
Output Price Cost per million output tokens	$6.00 / 1M	$10.00 / 1M
Blended Price Weighted 7:2:1 cache:input:output per 1M	$1.35 / 1M	$1.47 / 1M
Context Window Maximum input + output tokens	500K tokens~750 A4 pages of text	1M tokens~1,500 A4 pages of text
Max Output Tokens Per single request	66K	128K
Throughput Speed Tokens generated per second	110 tok/s	116 tok/s
SWE-bench Verified Real-world software engineering	77.2%	82.1%
GPQA Diamond Graduate-level reasoning	78.5%	80.6%
Cached Input Price Prompt caching discount per 1M tokens	$0.50 / 1M	$0.10 / 1M

¿Quién gana en cada área?

At-a-glance decision framework

Código

GPT-6 Sol

+4.9% SWE-bench lead

Costo

Grok 4.7

1.3x cheaper monthly runtime

Velocidad

GPT-6 Sol

+5% faster generation

Contexto

GPT-6 Sol

1M tokens window

Puntuaciones de Benchmarks Verificadas

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

Grok 4.7GPT-6 Sol

SWE-bench Verified (Autonomous Coding)

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

77.2%vs82.1%

GPQA Diamond (Doctorate-Level Science & Math)

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

78.5%vs80.6%

MMLU-Pro (Multi-task Language Understanding)

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

88.6%vs89.8%

LMSYS Chatbot Arena Elo

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

1465ptsvs1516pts

Humanity's Last Exam (Frontier Expert Knowledge)

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

15.2%vs18%

Terminal-Bench (Agentic Coding & Terminal Use)

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

38%vs63.2%

SciCode (Scientific Computing)

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

52.4%vs54.5%

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

76.5%vs79.5%

AIME (Advanced Math Competition)

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

91.2%vs93.4%

Long-Context Reasoning

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

89.5%vs90.8%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

110 tok/s vs116 tok/s

Latencia y Tiempo de Respuesta

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 4.70.62s

GPT-6 Sol1.16s

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

Grok 4.75.17s

GPT-6 Sol5.47s

Simulador Interactivo de Costos 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 4.7 Monthly API Bill

$9.15 / month

$2/1M in · $6/1M out

GPT-6 Sol Monthly API Bill

$12.15 / month

$2/1M in · $10/1M out

Grok 4.7 saves approximately $3.00 / month (25%) under this workload.1.3x Savings

Grok 4.7 · Strengths & Key Advantages

Ventana de contexto de 500K con hasta 66K tokens de salida máxima (SWE-bench Verified 77.2% · GPQA Diamond 78.5%)
Rendimiento ágil de 110 tokens/segundo con latencia inicial (TTFT) de solo 620 ms
Economía de API competitiva ($2/$6 por 1M de tokens) con soporte para caché de prompts y salidas JSON estructuradas

Considerations & Trade-offs

Modelo propietario en la nube; no permite descargar los pesos para ejecución local sin conexión
En volúmenes masivos de tokens, se recomienda activar el caché de prompts y Batch API para optimizar costos

GPT-6 Sol · Strengths & Key Advantages

Ventana de contexto de 1M con hasta 128K tokens de salida máxima (SWE-bench Verified 82.1% · GPQA Diamond 80.6%)
Rendimiento ágil de 116 tokens/segundo con latencia inicial (TTFT) de solo 1160 ms
Economía de API competitiva ($2/$10 por 1M de tokens) con soporte para caché de prompts y salidas JSON estructuradas

Considerations & Trade-offs

Modelo propietario en la nube; no permite descargar los pesos para ejecución local sin conexión
En volúmenes masivos de tokens, se recomienda activar el caché de prompts y Batch API para optimizar costos

Token Use & Task Economics

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

Metric	Grok 4.7	GPT-6 Sol
Cost per Task Estimated USD to finish one task	$0.68	$2.00
Output Tokens / Task Tokens generated per task	46K	62K
Reasoning Tokens / Task Thinking tokens burned per task	23K	36K

Especificaciones Técnicas

Architecture, release timeline, capabilities, and modalities.

Característica	Grok 4.7	GPT-6 Sol
Official API Model ID (SDK)	grok-4-7-latest	gpt-6-sol
API Protocol	xAI REST API (OpenAI-Compatible)	OpenAI Responses API & Chat Completions v1
Release Date	2026-09	2026-09
Knowledge Cutoff	April 2026	April 2026
Architecture	2.1T Multimodal Sparse MoE	Cost-efficient frontier unified reasoning model
Parameters	2.1T (MoE)	Confidential
Enterprise Rate Limits (RPM / TPM)	5,000 – 15,000 RPM (Production Tier) · 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 ($2/1M in) across full 500K window	Flat rate ($2/1M in) across full 1000K window
Prompt Cache Policy & TTL	Cached input at $0.5/1M tokens	Automatic prefix caching at $0.1/1M (no extra cache-write fee)
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 tool + Hosted Code Interpreter & File Search RAG
Official Fine-Tuning Support	API Prompt Engineering & RAG Distillation	Supervised Fine-Tuning (SFT), Direct Preference (DPO) & Reinforcement Fine-Tuning (RFT)
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	OpenAI Preparedness Framework Audited & System Card Published
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 4.7 vs GPT-6 Sol: Respuestas Rápidas (FAQ)

Which is more intelligent, Grok 4.7 or GPT-6 Sol?

GPT-6 Sol is more intelligent. It scores 93 compared with 46 on the composite Intelligence Index.

Which model is faster?

GPT-6 Sol is faster, generating 116 tokens per second compared with 110 tokens per second.

Which model is cheaper to run?

Grok 4.7 is cheaper at $1.35 per 1M tokens blended, compared with $1.47 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Grok 4.7 has lower latency, with a time to first token of 0.62s compared with 1.16s.

Which model has a larger context window?

GPT-6 Sol has a larger context window, supporting 1M tokens compared with 500K tokens.

Veredicto

Tanto Grok 4.7 (Ideal para razonamiento empresarial de frontera, programación avanzada y flujos de producción, sistemas RAG empresariales y automatización mediante API.) como GPT-6 Sol (Ideal para razonamiento empresarial de frontera, programación avanzada y flujos de producción, sistemas RAG empresariales y automatización mediante API.) destacan en producción: GPT-6 Sol lidera en inteligencia general y programación, GPT-6 Sol ofrece mayor velocidad de generación de tokens y Grok 4.7 resulta más rentable para cargas de trabajo API de alto volumen.

Preguntas frecuentes

¿Cuál es mejor para programación y razonamiento, Grok 4.7 o GPT-6 Sol?+

En las pruebas de inteligencia compuesta y resolución de código, GPT-6 Sol obtiene la ventaja. Puedes revisar la tabla SWE-bench y GPQA arriba para comparar cada métrica.

¿Cuánto cuesta la API de Grok 4.7 frente a GPT-6 Sol?+

Grok 4.7 cuesta $2.00 / $6.00 por millón de tokens de entrada/salida, mientras que GPT-6 Sol cuesta $2.00 / $10.00. En costo combinado, Grok 4.7 es la opción más económica.

¿Qué modelo tiene mayor ventana de contexto y menor latencia?+

Grok 4.7 cuenta con 500K tokens de contexto frente a 1M tokens de GPT-6 Sol. En velocidad de inferencia, GPT-6 Sol ofrece un rendimiento superior.

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 4.7 vs GPT-6 Sol

Cambia y Compara Cualquier Modelo

Grok 4.7

GPT-6 Sol

¿Quién gana en cada área?

Puntuaciones de Benchmarks Verificadas

Latencia y Tiempo de Respuesta

Simulador Interactivo de Costos de Tokens

Grok 4.7 · Strengths & Key Advantages

Considerations & Trade-offs

GPT-6 Sol · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Especificaciones Técnicas

Grok 4.7 vs GPT-6 Sol: Respuestas Rápidas (FAQ)

Veredicto

Preguntas frecuentes

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