Head-to-Head Model Comparison

Grok 4.6 vs Claude Opus 5.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

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

Compare Grok 4.6 by xAI against Claude Opus 5.5 by Anthropic across real-world coding, reasoning, token economics, and latency.

Comparación Directa (VS)

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xAI

Grok 4.6

Base más grande

1.5 billones parámetro Colossus-trained modelo fundacional ofreciendo reinforced codificación y profundo multi-hop razonamiento.

Intelligence Index77 / 100
Input Token:

$2.00 / 1M

Output Token:

$6.00 / 1M

Context Window:

500K tokens

SWE-bench Verified:

75.8%

Anthropic

Claude Opus 5.5

Titán de inteligencia de frontera

de Anthropic pinnacle modelo de frontera diseñado para de largo alcance agentic ingeniería de software, denso multimodal documento síntesis, y autónomo investigación flujos de trabajo.

Intelligence Index94 / 100
Input Token:

$4.00 / 1M

Output Token:

$20.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

84.6%

Diferencias Clave de un Vistazo

  • Grok 4.6 is 2.7x cheaper for API usage (input + output tokens combined).
  • Claude Opus 5.5 has a larger context window (1M vs 500K tokens).
  • Grok 4.6 is faster at 115 tok/s vs 78 tok/s.
  • Claude Opus 5.5 leads on SWE-bench coding (84.6% vs 75.8%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
CaracterísticaGrok 4.6Claude Opus 5.5
Intelligence Index
Composite reasoning & knowledge score (0-100)
7794
Provider
xAIAnthropic
Input Price
Cost per million input tokens
$2.00 / 1M$4.00 / 1M
Output Price
Cost per million output tokens
$6.00 / 1M$20.00 / 1M
Blended Price
Weighted 7:2:1 cache:input:output per 1M
$1.35 / 1M$3.08 / 1M
Context Window
Maximum input + output tokens
500K tokens~750 A4 pages of text1M tokens~1,500 A4 pages of text
Max Output Tokens
Per single request
66K128K
Throughput Speed
Tokens generated per second
115 tok/s78 tok/s
SWE-bench Verified
Real-world software engineering
75.8%84.6%
GPQA Diamond
Graduate-level reasoning
77.2%82.3%
Cached Input Price
Prompt caching discount per 1M tokens
$0.50 / 1M$0.40 / 1M

¿Quién gana en cada área?

At-a-glance decision framework
Código
Claude Opus 5.5
+8.8% SWE-bench lead
Costo
Grok 4.6
2.7x cheaper monthly runtime
Velocidad
Grok 4.6
+47% faster generation
Contexto
Claude Opus 5.5
1M tokens window

Puntuaciones de Benchmarks Verificadas

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

Grok 4.6Claude Opus 5.5
SWE-bench Verified (Autonomous Coding)

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

75.8%vs84.6%
GPQA Diamond (Doctorate-Level Science & Math)

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

77.2%vs82.3%
MMLU-Pro (Multi-task Language Understanding)

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

88%vs91.5%
LMSYS Chatbot Arena Elo

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

1450ptsvs1507pts
Humanity's Last Exam (Frontier Expert Knowledge)

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

14.8%vs19.8%
Terminal-Bench (Agentic Coding & Terminal Use)

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

51%vs66.4%
SciCode (Scientific Computing)

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

49.2%vs58.7%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

75%vs83.1%
AIME (Advanced Math Competition)

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

89.5%vs95.4%
Long-Context Reasoning

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

89%vs92.6%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

115 tok/s vs78 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 4.60.58s
Claude Opus 5.51.40s
Est. End-to-End Response (500 tokens)TTFT + generation time
Grok 4.64.93s
Claude Opus 5.57.81s

Simulador Interactivo de Costos 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 4.6 Monthly API Bill
$9.15 / month
$2/1M in · $6/1M out
Claude Opus 5.5 Monthly API Bill
$24.60 / month
$4/1M in · $20/1M out
Grok 4.6 saves approximately $15.45 / month (63%) under this workload.2.7x Savings

Grok 4.6 · Strengths & Key Advantages

  • masivo 1.5T parámetro capacidad proporcionando broader real-mundo knowledge y matiz
  • Preserves el attractive $2/$6 por millones token precio point
  • Notable improvements en completo-stack codificación y multifarchivo system arquitectura
Considerations & Trade-offs
  • Quickly succeeded por el 2.1T parámetro Grok 4.7 upgrade
  • ventana de contexto capped un 500K tokens

Claude Opus 5.5 · Strengths & Key Advantages

  • inigualable autónomo multipaso codificación agéntica y refactorización
  • Flawless multidocumento razonamiento sobre 1M token contexto con no largo-prompt surcharge
  • más alto Artificial análisis inteligencia Index ever measured (58/100), leading SWE-bench Pro un 89.9%
  • Precise herramienta ejecución con robust error-recovery bucles
Considerations & Trade-offs
  • Premium salida precios ($20.00/M) plus heavy razonamiento-token usage (~119K salida tokens por index tarea) keeps largo agentic se ejecuta expensive
  • largo pensamiento times un maximum effort puede push un único hard agentic tarea toward ~$13

Token Use & Task Economics

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

MetricGrok 4.6Claude Opus 5.5
Cost per Task
Estimated USD to finish one task
$0.65$3.85
Output Tokens / Task
Tokens generated per task
45K68K
Reasoning Tokens / Task
Thinking tokens burned per task
22K42K

Especificaciones Técnicas

Architecture, release timeline, capabilities, and modalities.

CaracterísticaGrok 4.6Claude Opus 5.5
Official API Model ID (SDK)grok-4-6-latestclaude-opus-5-5-20260901
API ProtocolxAI REST API (OpenAI-Compatible)Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date2026-082026-09
Knowledge CutoffApril 2026June 2026
Architecture1.5T Colossus Sparse MoEExtended Autonomous Hybrid Reasoning Transformer
Parameters1.5T (MoE)Confidential
Enterprise Rate Limits (RPM / TPM)5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM4,000 – 10,000 RPM (Tier 4 + Priority Tier) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($2/1M in) across full 500K windowStandard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTLCached input at $0.5/1M tokens$0.4/1M cached read (90% off); 5-min default & 1-hour extended 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 ExecutionNative Web Search Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning SupportAPI Prompt Engineering & RAG DistillationCustom Model Tuning via Amazon Bedrock & Prompt 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)
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 VerifiedAnthropic 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 TierSOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalitiestext, visiontext, vision
Output Modalitiestexttext

Grok 4.6 vs Claude Opus 5.5: Respuestas Rápidas (FAQ)

Which is more intelligent, Grok 4.6 or Claude Opus 5.5?

Claude Opus 5.5 is more intelligent. It scores 94 compared with 77 on the composite Intelligence Index.

Which model is faster?

Grok 4.6 is faster, generating 115 tokens per second compared with 78 tokens per second.

Which model is cheaper to run?

Grok 4.6 is cheaper at $1.35 per 1M tokens blended, compared with $3.08 (7:2:1 cache:input:output ratio).

Which model has lower latency?

Grok 4.6 has lower latency, with a time to first token of 0.58s compared with 1.40s.

Which model has a larger context window?

Claude Opus 5.5 has a larger context window, supporting 1M tokens compared with 500K tokens.

Veredicto

Choose Grok 4.6 for medium-un-grande ingeniería de software tareas, datos síntesis, y complejo análisis, or choose Claude Opus 5.5 for grande-escala software development agentes, empresarial codebases, y de misión crítica científico síntesis.

Preguntas frecuentes

Which is cheaper: Grok 4.6 or Claude Opus 5.5?+

Grok 4.6 costs $2/1M input and $6/1M output tokens, while Claude Opus 5.5 costs $4/1M input and $20/1M output tokens.

Which model has a larger context window: Grok 4.6 or Claude Opus 5.5?+

Grok 4.6 supports 500K tokens whereas Claude Opus 5.5 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.

Las puntuaciones de benchmarks, precios por token y límites de tasa evolucionan rápidamente. Verifique siempre las especificaciones actuales en la documentación oficial del proveedor.

Fuentes: xAI & Anthropic Official Documentation