Head-to-Head Model Comparison

Grok 4.6 vs Grok-4

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Ditinjau oleh tim riset GetInfoUsPeninjauan terakhir: October 2026Kebijakan editorial
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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 dari xAI dan Grok-4 dari xAI adalah dua model AI unggulan. Grok 4.6 menawarkan jendela konteks 500K token dengan harga $2.00/$6.00 per 1 juta token, sedangkan Grok-4 menyediakan konteks 1M token seharga $2.50/$10.00 per 1 juta token. Berikut perbandingan lengkap benchmark, latensi, dan biayanya.

Perbandingan Langsung (VS)

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Grok 4.6

Model Unggulan Garis Depan

Grok 4.6 dari xAI adalah model AI yang dirancang untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, menghadirkan jendela konteks 500K, kecepatan 115 token/detik, indeks kecerdasan 77/100, serta tarif $2/$6

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

Model Unggulan Garis Depan

Grok-4 dari xAI adalah model AI yang dirancang untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, menghadirkan jendela konteks 1M, kecepatan 125 token/detik, indeks kecerdasan 92/100, serta tarif $2.5/$10 p

Intelligence Index92 / 100
Input Token:

$2.50 / 1M

Output Token:

$10.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

76.5%

Perbedaan Utama Sekilas

  • 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

Siapa Unggul di Mana?

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

Skor Benchmark Terverifikasi

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

Latensi & Waktu Respons

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

Simulator Biaya Token Interaktif

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

  • Jendela konteks 500K dengan kapasitas output maksimum hingga 66K token (SWE-bench Verified 75.8% · GPQA Diamond 77.2%)
  • Kecepatan generasi tinggi 115 token/detik dengan latensi token pertama (TTFT) hanya 580 ms
  • Skema harga API kompetitif (tarif $2/$6 per 1M token) dengan dukungan cache prompt dan output JSON terstruktur
Considerations & Trade-offs
  • Model cloud proprietari tertutup; bobot model tidak dapat diunduh untuk penggunaan lokal offline
  • Untuk trafik produksi skala besar, disarankan mengaktifkan fitur Prompt Caching dan Batch API guna menghemat biaya

Grok-4 · Strengths & Key Advantages

  • Jendela konteks 1M dengan kapasitas output maksimum hingga 64K token (SWE-bench Verified 76.5% · GPQA Diamond 77.8%)
  • Kecepatan generasi tinggi 125 token/detik dengan latensi token pertama (TTFT) hanya 680 ms
  • Skema harga API kompetitif (tarif $2.5/$10 per 1M token) dengan dukungan cache prompt dan output JSON terstruktur
Considerations & Trade-offs
  • Model cloud proprietari tertutup; bobot model tidak dapat diunduh untuk penggunaan lokal offline
  • Untuk trafik produksi skala besar, disarankan mengaktifkan fitur Prompt Caching dan Batch API guna menghemat biaya

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

Spesifikasi Teknis

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: Jawaban Cepat (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.

Kesimpulan

Baik Grok 4.6 (Sangat cocok untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, sistem RAG perusahaan, dan integrasi API skala produksi.) maupun Grok-4 (Sangat cocok untuk penalaran perusahaan garis depan, pemrograman tingkat lanjut, dan produksi AI, sistem RAG perusahaan, dan integrasi API skala produksi.) sangat tangguh: Grok-4 unggul dalam penalaran dan pemrograman, Grok-4 memberikan kecepatan generasi token lebih tinggi, dan Grok 4.6 lebih hemat biaya untuk penggunaan API skala besar.

Pertanyaan Umum (FAQ)

Mana yang lebih baik untuk coding dan penalaran, Grok 4.6 atau Grok-4?+

Dalam indeks kecerdasan gabungan dan benchmark coding, Grok-4 memimpin. Lihat skor SWE-bench dan GPQA di atas untuk detailnya.

Berapa perbandingan harga API Grok 4.6 vs Grok-4?+

Grok 4.6 mengenakan biaya $2.00 / $6.00 per 1M token input/output, sedangkan Grok-4 sebesar $2.50 / $10.00. Secara keseluruhan, Grok 4.6 lebih hemat biaya.

Model mana yang memiliki jendela konteks lebih besar dan kecepatan lebih tinggi?+

Grok 4.6 mendukung konteks 500K token dibandingkan 1M token pada Grok-4, sementara Grok-4 unggul dalam kecepatan output token per detik.

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.

Sumber resmi: Dokumentasi API resmi xAI & xAI serta evaluasi benchmark independen (2026).