Head-to-Head Model Comparison

Grok 4.20 (Reasoning) vs GPT-6 Sol

Benchmarks, API Token Pricing, Context Window & Speed Comparison

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

Compare Grok 4.20 (Reasoning) by xAI against GPT-6 Sol by OpenAI across real-world coding, reasoning, token economics, and latency.

Comparação Direta (VS)

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xAI

Grok 4.20 (Reasoning)

Modelo de Raciocínio Profundo

O Grok 4.20 (Reasoning) da xAI é um modelo de inteligência artificial com janela de contexto de 1M tokens e preço de API de $1.25/1M na entrada e $2.5/1M na saída, projetado para programação, raciocínio e automação empresarial.

Intelligence Index68 / 100
Input Token:

$3.00 / 1M

Output Token:

$15.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

68.2%

OpenAI

GPT-6 Sol

Modelo de Raciocínio Profundo

O GPT-6 Sol da OpenAI é um modelo de inteligência artificial com janela de contexto de 1M tokens e preço de API de $2.0/1M na entrada e $10.0/1M na saída, projetado para programação, raciocínio e automação empresarial.

Intelligence Index93 / 100
Input Token:

$2.00 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

82.1%

Principais Diferenças em Resumo

  • GPT-6 Sol is 1.6x cheaper for API usage (input + output tokens combined).
  • GPT-6 Sol is faster at 116 tok/s vs 95 tok/s.
  • GPT-6 Sol leads on SWE-bench coding (82.1% vs 68.2%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGrok 4.20 (Reasoning)GPT-6 Sol
Intelligence Index
Composite reasoning & knowledge score (0-100)
6893
Provider
xAIOpenAI
Input Price
Cost per million input tokens
$3.00 / 1M$2.00 / 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$1.47 / 1M
Context Window
Maximum input + output tokens
1M tokens~1,500 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
66K128K
Throughput Speed
Tokens generated per second
95 tok/s116 tok/s
SWE-bench Verified
Real-world software engineering
68.2%82.1%
GPQA Diamond
Graduate-level reasoning
72.8%80.6%
Cached Input Price
Prompt caching discount per 1M tokens
$0.75 / 1M$0.10 / 1M

Quem vence em cada categoria?

At-a-glance decision framework
Coding
GPT-6 Sol
+13.9% SWE-bench lead
Cost
GPT-6 Sol
1.6x cheaper monthly runtime
Speed
GPT-6 Sol
+22% faster generation
Context
Tied
1M tokens window

Pontuações de Benchmarks Verificadas

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

Grok 4.20 (Reasoning)GPT-6 Sol
SWE-bench Verified (Autonomous Coding)

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

68.2%vs82.1%
GPQA Diamond (Doctorate-Level Science & Math)

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

72.8%vs80.6%
MMLU-Pro (Multi-task Language Understanding)

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

84.1%vs89.8%
LMSYS Chatbot Arena Elo

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

1395ptsvs1516pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

11.8%vs18%
Terminal-Bench (Agentic Coding & Terminal Use)

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

44.5%vs63.2%
SciCode (Scientific Computing)

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

41.2%vs54.5%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

66.5%vs79.5%
AIME (Advanced Math Competition)

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

86.4%vs93.4%
Long-Context Reasoning

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

89.2%vs90.8%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

95 tok/s vs116 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 4.20 (Reasoning)0.98s
GPT-6 Sol1.16s
Est. End-to-End Response (500 tokens)TTFT + generation time
Grok 4.20 (Reasoning)6.24s
GPT-6 Sol5.47s

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 4.20 (Reasoning) Monthly API Bill
$19.13 / month
$3/1M in · $15/1M out
GPT-6 Sol Monthly API Bill
$12.15 / month
$2/1M in · $10/1M out
GPT-6 Sol saves approximately $6.97 / month (36%) under this workload.1.6x Savings

Grok 4.20 (Reasoning) · Strengths & Key Advantages

  • Arquitetura Colossus-Scale Reasoning Sparse MoE avançada da xAI com contexto de 1M tokens
  • Excelente relação custo-benefício ($1.25/1M entrada, $2.5/1M saída) e baixa latência
  • Forte desempenho em benchmarks de código, análise lógica e tarefas multilíngues
Considerations & Trade-offs
  • Cargas de trabalho com contexto máximo exigem monitoramento de custos de tokens
  • Requer engenharia de prompt adequada para fluxos de trabalho altamente específicos

GPT-6 Sol · Strengths & Key Advantages

  • Arquitetura Cost-efficient frontier unified reasoning model avançada da OpenAI com contexto de 1M tokens
  • Excelente relação custo-benefício ($2.0/1M entrada, $10.0/1M saída) e baixa latência
  • Forte desempenho em benchmarks de código, análise lógica e tarefas multilíngues
Considerations & Trade-offs
  • Cargas de trabalho com contexto máximo exigem monitoramento de custos de tokens
  • Requer engenharia de prompt adequada para fluxos de trabalho altamente específicos

Token Use & Task Economics

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

MetricGrok 4.20 (Reasoning)GPT-6 Sol
Cost per Task
Estimated USD to finish one task
$1.45$2.00
Output Tokens / Task
Tokens generated per task
45K62K
Reasoning Tokens / Task
Thinking tokens burned per task
28K36K

Especificações Técnicas

Architecture, release timeline, capabilities, and modalities.

FeatureGrok 4.20 (Reasoning)GPT-6 Sol
Official API Model ID (SDK)grok-4-20-reasoning-latestgpt-6-sol
API ProtocolxAI REST API (OpenAI-Compatible)OpenAI Responses API & Chat Completions v1
Release Date2026-032026-09
Knowledge CutoffNovember 2025April 2026
ArchitectureColossus-Scale Reasoning Sparse MoECost-efficient frontier unified reasoning model
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) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($3/1M in) across full 1000K windowFlat rate ($2/1M in) across full 1000K window
Prompt Cache Policy & TTLCached input at $0.75/1M tokensAutomatic prefix caching at $0.1/1M (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)
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
Output Modalitiestexttext

Grok 4.20 (Reasoning) vs GPT-6 Sol: Respostas Rápidas (FAQ)

Which is more intelligent, Grok 4.20 (Reasoning) or GPT-6 Sol?

GPT-6 Sol is more intelligent. It scores 93 compared with 68 on the composite Intelligence Index.

Which model is faster?

GPT-6 Sol is faster, generating 116 tokens per second compared with 95 tokens per second.

Which model is cheaper to run?

GPT-6 Sol is cheaper at $1.47 per 1M tokens blended, compared with $2.63 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Grok 4.20 (Reasoning) has lower latency, with a time to first token of 0.98s compared with 1.16s.

Veredito

Choose Grok 4.20 (Reasoning) for automação corporativa, engenharia de software, agentes autônomos e pipelines de produção com xai, or choose GPT-6 Sol for automação corporativa, engenharia de software, agentes autônomos e pipelines de produção com openai.

Perguntas Frequentes (FAQ)

Which is cheaper: Grok 4.20 (Reasoning) or GPT-6 Sol?+

Grok 4.20 (Reasoning) costs $3/1M input and $15/1M output tokens, while GPT-6 Sol costs $2/1M input and $10/1M output tokens.

Which model has a larger context window: Grok 4.20 (Reasoning) or GPT-6 Sol?+

Grok 4.20 (Reasoning) supports 1M tokens whereas GPT-6 Sol supports 1M tokens.

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: xAI & OpenAI Official Documentation