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Head-to-Head Model Comparison

Grok 4.6 vs Grok-4

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Verificato dal team di ricerca di GetInfoUsUltima verifica: October 2026Politica editoriale
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AI CompareAI BenchmarkToken PricingModel CostModel SpecsSWE-bench CodingModel VersusWhich AI ModelLLM Speed & LatencyReasoning ModelsExtended ThinkingPrompt Caching ROI
Grok 4.6 vs Grok-4: Benchmarks, Pricing & Speed Comparison

Grok 4.6 di xAI e Grok-4 di xAI sono due modelli di IA di riferimento. Grok 4.6 offre una finestra di contesto di 500K token a $2.00/$6.00 per milione di token, mentre Grok-4 mette a disposizione 1M token di contesto a $2.50/$10.00 per milione di token. Di seguito analizziamo benchmark, latenza e costi.

Confronto Diretto (VS)

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Grok 4.6

Modello Ammiraglia di Frontiera

Grok 4.6 di xAI è un modello di IA progettato per il ragionamento aziendale di frontiera, la programmazione avanzata e i carichi di produzione, con finestra di contesto da 500K, velocità di 115 token/s, indice di intelligenza di 77/100 e ta

Intelligence Index77 / 100
Input Token:

$2.00 / 1M

Output Token:

$6.00 / 1M

Context Window:

500K tokens

SWE-bench Verified:

75.8%

xAI

Grok-4

Modello Ammiraglia di Frontiera

Grok-4 di xAI è un modello di IA progettato per il ragionamento aziendale di frontiera, la programmazione avanzata e i carichi di produzione, con finestra di contesto da 1M, velocità di 125 token/s, indice di intelligenza di 92/100 e tariff

Intelligence Index92 / 100
Input Token:

$2.50 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

76.5%

Differenze Chiave a Colpo d’Occhio

  • Grok 4.6 is 1.4x cheaper for API usage (input + output tokens combined).
  • Grok-4 has a larger context window (1M vs 500K tokens).
  • Grok-4 is faster at 125 tok/s vs 115 tok/s.
  • Grok-4 leads on SWE-bench coding (76.5% vs 75.8%).
Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →
FeatureGrok 4.6Grok-4
Intelligence Index
Composite reasoning & knowledge score (0-100)
7792
Provider
xAIxAI
Input Price
Cost per million input tokens
$2.00 / 1M$2.50 / 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$1.68 / 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
66K64K
Throughput Speed
Tokens generated per second
115 tok/s125 tok/s
SWE-bench Verified
Real-world software engineering
75.8%76.5%
GPQA Diamond
Graduate-level reasoning
77.2%77.8%
Cached Input Price
Prompt caching discount per 1M tokens
$0.50 / 1M$0.25 / 1M

Chi vince in ogni categoria?

At-a-glance decision framework
Coding
Grok-4
+0.7% SWE-bench lead
Cost
Grok 4.6
1.4x cheaper monthly runtime
Speed
Grok-4
+9% faster generation
Context
Grok-4
1M tokens window

Punteggi Benchmark Verificati

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

Grok 4.6Grok-4
SWE-bench Verified (Autonomous Coding)

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

75.8%vs76.5%
GPQA Diamond (Doctorate-Level Science & Math)

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

77.2%vs77.8%
MMLU-Pro (Multi-task Language Understanding)

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

88%vs87.4%
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%vs15.6%
Terminal-Bench (Agentic Coding & Terminal Use)

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

51%vs54.2%
SciCode (Scientific Computing)

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

49.2%vs48.7%
LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

75%vs75.3%
AIME (Advanced Math Competition)

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

89.5%vs89.2%
Long-Context Reasoning

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

89%vs86.5%
Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

115 tok/s vs125 tok/s

Latenza e Tempo di Risposta

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
Grok-40.68s
Est. End-to-End Response (500 tokens)TTFT + generation time
Grok 4.64.93s
Grok-44.68s

Simulatore Interattivo dei Costi Token

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
Grok-4 Monthly API Bill
$13.13 / month
$2.5/1M in · $10/1M out
Grok 4.6 saves approximately $3.97 / month (30%) under this workload.1.4x Savings

Grok 4.6 · Strengths & Key Advantages

  • Finestra di contesto da 500K con capacità massima di output fino a 66K token (SWE-bench Verified 75.8% · GPQA Diamond 77.2%)
  • Throughput elevato di 115 token/secondo con latenza al primo token (TTFT) di soli 580 ms
  • Economia API competitiva ($2/$6 per 1M di token) con supporto per prompt caching, tool calling e output JSON strutturati
Considerations & Trade-offs
  • Modello cloud proprietario chiuso; non consente il download locale dei pesi per l’esecuzione offline
  • Per volumi di traffico elevati in produzione si consiglia di attivare il prompt caching e la Batch API

Grok-4 · Strengths & Key Advantages

  • Finestra di contesto da 1M con capacità massima di output fino a 64K token (SWE-bench Verified 76.5% · GPQA Diamond 77.8%)
  • Throughput elevato di 125 token/secondo con latenza al primo token (TTFT) di soli 680 ms
  • Economia API competitiva ($2.5/$10 per 1M di token) con supporto per prompt caching, tool calling e output JSON strutturati
Considerations & Trade-offs
  • Modello cloud proprietario chiuso; non consente il download locale dei pesi per l’esecuzione offline
  • Per volumi di traffico elevati in produzione si consiglia di attivare il prompt caching e la Batch API

Token Use & Task Economics

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

MetricGrok 4.6Grok-4
Cost per Task
Estimated USD to finish one task
$0.65$1.65
Output Tokens / Task
Tokens generated per task
45K48K
Reasoning Tokens / Task
Thinking tokens burned per task
22K24K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

FeatureGrok 4.6Grok-4
Official API Model ID (SDK)grok-4-6-latestgrok-4-latest
API ProtocolxAI REST API (OpenAI-Compatible)xAI REST API (OpenAI-Compatible)
Release Date2026-082026-07
Knowledge CutoffApril 2026Real-time (Up to October 2026)
Architecture1.5T Colossus Sparse MoEColossus-Scale Dense Mixture-of-Experts
Parameters1.5T (MoE)Confidential
Enterprise Rate Limits (RPM / TPM)5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM5,000 – 15,000 RPM (Production Tier) · 4,000,000 – 10,000,000 TPM
Long-Context Tier (>128K/200K)Flat rate ($2/1M in) across full 500K windowFlat rate ($2.5/1M in) across full 1000K window
Prompt Cache Policy & TTLCached input at $0.5/1M tokensCached input at $0.25/1M tokens
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 ExecutionReal-time Web & X (Twitter) Search Grounding + Code Execution
Official Fine-Tuning SupportAPI Prompt Engineering & RAG DistillationAPI Prompt Engineering & RAG 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 VerifiedxAI Production Safety & Alignment 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
Output Modalitiestexttext

Grok 4.6 vs Grok-4: Risposte Rapide (FAQ)

Which is more intelligent, Grok 4.6 or Grok-4?

Grok-4 is more intelligent. It scores 92 compared with 77 on the composite Intelligence Index.

Which model is faster?

Grok-4 is faster, generating 125 tokens per second compared with 115 tokens per second.

Which model is cheaper to run?

Grok 4.6 is cheaper at $1.35 per 1M tokens blended, compared with $1.68 (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 0.68s.

Which model has a larger context window?

Grok-4 has a larger context window, supporting 1M tokens compared with 500K tokens.

Verdetto

Sia Grok 4.6 (Ideale per il ragionamento aziendale di frontiera, la programmazione avanzata e i carichi di produzione, sistemi RAG aziendali e integrazioni API scalabili.) sia Grok-4 (Ideale per il ragionamento aziendale di frontiera, la programmazione avanzata e i carichi di produzione, sistemi RAG aziendali e integrazioni API scalabili.) eccellono in produzione: Grok-4 guida nei benchmark di ragionamento e programmazione, Grok-4 garantisce una generazione più rapida e Grok 4.6 offre il miglior rapporto qualità-prezzo per carichi API elevati.

Domande Frequenti (FAQ)

Quale modello è migliore per coding e ragionamento, Grok 4.6 o Grok-4?+

Nell’indice di intelligenza composito e nei benchmark di programmazione prevale Grok-4. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.

Qual è la differenza di prezzo API tra Grok 4.6 e Grok-4?+

Grok 4.6 costa $2.00 / $6.00 per milione di token di input/output, mentre Grok-4 costa $2.50 / $10.00. Nel costo combinato, Grok 4.6 risulta più economico.

Quale modello ha la finestra di contesto più ampia e la velocità maggiore?+

Grok 4.6 supporta 500K token di contesto contro 1M token di Grok-4, mentre Grok-4 offre una velocità di generazione superiore.

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 & PricingContext WindowAI BenchmarksReasoning ModelsTool CallingModel Context Protocol (MCP)

Related reading

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.

Fonti ufficiali: Documentazione API ufficiale di xAI e xAI, schede di sistema e benchmark indipendenti (2026).