Head-to-Head Model Comparison

Grok Build 0.1 vs Gemini 4 Argon

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Revisado pela equipe de pesquisa do GetInfoUsÚltima revisão: October 2026Política editorial
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Compare Grok Build 0.1 by xAI against Gemini 4 Argon by Google across real-world coding, reasoning, token economics, and latency.

Comparação Direta (VS)

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xAI

Grok Build 0.1

Modelo de Raciocínio Profundo

O Grok Build 0.1 da xAI é um modelo de inteligência artificial com janela de contexto de 256K tokens e preço de API de $1.0/1M na entrada e $2.0/1M na saída, projetado para programação, raciocínio e automação empresarial.

Intelligence Index65 / 100
Input Token:

$1.00 / 1M

Output Token:

$2.00 / 1M

Context Window:

256K tokens

SWE-bench Verified:

69.8%

Google

Gemini 4 Argon

Modelo de Raciocínio Profundo

O Gemini 4 Argon da Google é um modelo de inteligência artificial com janela de contexto de 1M tokens e preço de API de $2/1M na entrada e $10/1M na saída, projetado para programação, raciocínio e automação empresarial.

Intelligence Index97 / 100
Input Token:

$2.00 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

81.9%

Principais Diferenças em Resumo

  • Grok Build 0.1 is 3.3x cheaper for API usage (input + output tokens combined).
  • Gemini 4 Argon has a larger context window (1M vs 256K tokens).
  • Grok Build 0.1 is faster at 120 tok/s vs 115 tok/s.
  • Gemini 4 Argon leads on SWE-bench coding (81.9% vs 69.8%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGrok Build 0.1Gemini 4 Argon
Intelligence Index
Composite reasoning & knowledge score (0-100)
6597
Provider
xAIGoogle
Input Price
Cost per million input tokens
$1.00 / 1M$2.00 / 1M
Output Price
Cost per million output tokens
$2.00 / 1M$10.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$0.57 / 1M$1.47 / 1M
Context Window
Maximum input + output tokens
256K tokens~384 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
66K1000K
Throughput Speed
Tokens generated per second
120 tok/s115 tok/s
SWE-bench Verified
Real-world software engineering
69.8%81.9%
GPQA Diamond
Graduate-level reasoning
68.2%81.5%
Cached Input Price
Prompt caching discount per 1M tokens
$0.25 / 1M$0.10 / 1M

Quem vence em cada categoria?

At-a-glance decision framework
Coding
Gemini 4 Argon
+12.1% SWE-bench lead
Cost
Grok Build 0.1
3.3x cheaper monthly runtime
Speed
Grok Build 0.1
+4% faster generation
Context
Gemini 4 Argon
1M tokens window

Pontuações de Benchmarks Verificadas

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

Grok Build 0.1Gemini 4 Argon
SWE-bench Verified (Autonomous Coding)

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

69.8%vs81.9%
GPQA Diamond (Doctorate-Level Science & Math)

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

68.2%vs81.5%
MMLU-Pro (Multi-task Language Understanding)

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

82.5%vs90.8%
LMSYS Chatbot Arena Elo

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

1375ptsvs1525pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

10.5%vs18.9%
Terminal-Bench (Agentic Coding & Terminal Use)

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

46.2%vs57.4%
SciCode (Scientific Computing)

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

42%vs56.4%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

68.5%vs80.5%
AIME (Advanced Math Competition)

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

82.1%vs94.8%
Long-Context Reasoning

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

80.4%vs96.4%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

120 tok/s vs115 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 Build 0.10.55s
Gemini 4 Argon0.85s
Est. End-to-End Response (500 tokens)TTFT + generation time
Grok Build 0.14.72s
Gemini 4 Argon5.20s

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 Build 0.1 Monthly API Bill
$3.67 / month
$1/1M in · $2/1M out
Gemini 4 Argon Monthly API Bill
$12.15 / month
$2/1M in · $10/1M out
Grok Build 0.1 saves approximately $8.48 / month (70%) under this workload.3.3x Savings

Grok Build 0.1 · Strengths & Key Advantages

  • Arquitetura Code-Specialized Autoregressive Transformer avançada da xAI com contexto de 256K tokens
  • Excelente relação custo-benefício ($1.0/1M entrada, $2.0/1M 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

Gemini 4 Argon · Strengths & Key Advantages

  • Arquitetura Pathways Multimodal Sparse Mixture-of-Experts avançada da Google com contexto de 1M tokens
  • Excelente relação custo-benefício ($2/1M entrada, $10/1M 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 Build 0.1Gemini 4 Argon
Cost per Task
Estimated USD to finish one task
$0.95$2.45
Output Tokens / Task
Tokens generated per task
42K75K
Reasoning Tokens / Task
Thinking tokens burned per task
18K36K

Especificações Técnicas

Architecture, release timeline, capabilities, and modalities.

FeatureGrok Build 0.1Gemini 4 Argon
Official API Model ID (SDK)grok-build-0-1-latestmodels/gemini-4-argon
API ProtocolxAI REST API (OpenAI-Compatible)Google Gemini API (generateContent) + OpenAI-Compatible SDK
Release Date2026-042026-09
Knowledge CutoffJanuary 2026June 2026
ArchitectureCode-Specialized Autoregressive TransformerPathways Multimodal Sparse Mixture-of-Experts
ParametersConfidentialConfidential
Enterprise Rate Limits (RPM / TPM)5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM10,000 – 30,000 RPM (Tier 5 Enterprise) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($1/1M in) across full 256K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLCached input at $0.25/1M tokensImplicit + Explicit Context Caching at $0.1/1M with configurable TTL
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 ExecutionBuilt-in Google Search Grounding + Managed Python Code Execution Sandbox
Official Fine-Tuning SupportAPI Prompt Engineering & RAG DistillationVertex AI Supervised Adapter Tuning & Context Distillation
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) · Video (~258–300 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 VerifiedGoogle DeepMind Frontier Safety Framework Verified
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, video
Output Modalitiestexttext

Grok Build 0.1 vs Gemini 4 Argon: Respostas Rápidas (FAQ)

Which is more intelligent, Grok Build 0.1 or Gemini 4 Argon?

Gemini 4 Argon is more intelligent. It scores 97 compared with 65 on the composite Intelligence Index.

Which model is faster?

Grok Build 0.1 is faster, generating 120 tokens per second compared with 115 tokens per second.

Which model is cheaper to run?

Grok Build 0.1 is cheaper at $0.57 per 1M tokens blended, compared with $1.47 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Grok Build 0.1 has lower latency, with a time to first token of 0.55s compared with 0.85s.

Which model has a larger context window?

Gemini 4 Argon has a larger context window, supporting 1M tokens compared with 256K tokens.

Veredito

Choose Grok Build 0.1 for automação corporativa, engenharia de software, agentes autônomos e pipelines de produção com xai, or choose Gemini 4 Argon for automação corporativa, engenharia de software, agentes autônomos e pipelines de produção com google.

Perguntas Frequentes (FAQ)

Which is cheaper: Grok Build 0.1 or Gemini 4 Argon?+

Grok Build 0.1 costs $1/1M input and $2/1M output tokens, while Gemini 4 Argon costs $2/1M input and $10/1M output tokens.

Which model has a larger context window: Grok Build 0.1 or Gemini 4 Argon?+

Grok Build 0.1 supports 256K tokens whereas Gemini 4 Argon 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 & Google Official Documentation