Head-to-Head Model Comparison

Grok 4.7 vs Claude Opus 5.5

Benchmarks, API Token Pricing, Context Window & Speed Comparison

Verificato dal team di ricerca di GetInfoUsUltima verifica: October 2026Politica editoriale

Cambia e Confronta Qualsiasi Modello

Select any AI models from our verified benchmark database to generate live side-by-side matrices.

Grok 4.7Profile

Claude Opus 5.5Profile

Multi-Model Arena Stack:

5-Model Matrix Workbench

Popular Matchups:

xAI

Grok 4.7

Modello Ammiraglia di Frontiera

Grok 4.7 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 110 token/s, indice di intelligenza di 46/100 e ta

Intelligence Index46 / 100

Input Token:

$2.00 / 1M

Output Token:

$6.00 / 1M

Context Window:

500K tokens

SWE-bench Verified:

77.2%

Anthropic

Claude Opus 5.5

Modello Ammiraglia di Frontiera

Claude Opus 5.5 di Anthropic 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 78 token/s, indice di intelligenza di 9

Intelligence Index94 / 100

Input Token:

$4.00 / 1M

Output Token:

$20.00 / 1M

Context Window:

1M tokens

SWE-bench Verified:

84.6%

Differenze Chiave a Colpo d’Occhio

Grok 4.7 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 4.7 is faster at 110 tok/s vs 78 tok/s.
Claude Opus 5.5 leads on SWE-bench coding (84.6% vs 77.2%).

Need definitions for token pricing, context, or benchmarks?Explore AI Glossary →

Feature	Grok 4.7	Claude Opus 5.5
Intelligence Index Composite reasoning & knowledge score (0-100)	46	94
Provider	xAI	Anthropic
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 text	1M tokens~1,500 A4 pages of text
Max Output Tokens Per single request	66K	128K
Throughput Speed Tokens generated per second	110 tok/s	78 tok/s
SWE-bench Verified Real-world software engineering	77.2%	84.6%
GPQA Diamond Graduate-level reasoning	78.5%	82.3%
Cached Input Price Prompt caching discount per 1M tokens	$0.50 / 1M	$0.40 / 1M

Chi vince in ogni categoria?

At-a-glance decision framework

Coding

Claude Opus 5.5

+7.4% SWE-bench lead

Cost

Grok 4.7

2.7x cheaper monthly runtime

Speed

Grok 4.7

+41% faster generation

Context

Claude Opus 5.5

1M tokens window

Punteggi Benchmark Verificati

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

Grok 4.7Claude Opus 5.5

SWE-bench Verified (Autonomous Coding)

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

77.2%vs84.6%

GPQA Diamond (Doctorate-Level Science & Math)

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

78.5%vs82.3%

MMLU-Pro (Multi-task Language Understanding)

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

88.6%vs91.5%

LMSYS Chatbot Arena Elo

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

1465ptsvs1507pts

Humanity's Last Exam (Frontier Expert Knowledge)

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

15.2%vs19.8%

Terminal-Bench (Agentic Coding & Terminal Use)

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

38%vs66.4%

SciCode (Scientific Computing)

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

52.4%vs58.7%

LiveCodeBench (Competitive Coding)

Contamination-free competitive programming problems collected continuously over time.

76.5%vs83.1%

AIME (Advanced Math Competition)

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

91.2%vs95.4%

Long-Context Reasoning

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

89.5%vs92.6%

Generation Speed (Throughput)

Tokens emitted per second during active generation streaming.

110 tok/s vs78 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 4.70.62s

Claude Opus 5.51.40s

Est. End-to-End Response (500 tokens)TTFT + generation time

Grok 4.75.17s

Claude Opus 5.57.81s

Simulatore Interattivo dei Costi Token

Adjust sliders to calculate projected monthly cloud API spending with prompt caching discounts.

Daily Input Tokens100K / day

10K500K1M

Daily Output Tokens30K / day

5K150K300K

Prompt Cache Hit Ratio50% cached

0% (Cold)50%90% (Warm)

Grok 4.7 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 4.7 saves approximately $15.45 / month (63%) under this workload.2.7x Savings

Grok 4.7 · Strengths & Key Advantages

Finestra di contesto da 500K con capacità massima di output fino a 66K token (SWE-bench Verified 77.2% · GPQA Diamond 78.5%)
Throughput elevato di 110 token/secondo con latenza al primo token (TTFT) di soli 620 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

Claude Opus 5.5 · Strengths & Key Advantages

Finestra di contesto da 1M con capacità massima di output fino a 128K token (SWE-bench Verified 84.6% · GPQA Diamond 82.3%)
Throughput elevato di 78 token/secondo con latenza al primo token (TTFT) di soli 1400 ms
Economia API competitiva ($4/$20 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.

Metric	Grok 4.7	Claude Opus 5.5
Cost per Task Estimated USD to finish one task	$0.68	$3.85
Output Tokens / Task Tokens generated per task	46K	68K
Reasoning Tokens / Task Thinking tokens burned per task	23K	42K

Specifiche Tecniche

Architecture, release timeline, capabilities, and modalities.

Feature	Grok 4.7	Claude Opus 5.5
Official API Model ID (SDK)	grok-4-7-latest	claude-opus-5-5-20260901
API Protocol	xAI REST API (OpenAI-Compatible)	Anthropic Messages API + AWS Bedrock + Vertex AI
Release Date	2026-09	2026-09
Knowledge Cutoff	April 2026	June 2026
Architecture	2.1T Multimodal Sparse MoE	Extended Autonomous Hybrid Reasoning Transformer
Parameters	2.1T (MoE)	Confidential
Enterprise Rate Limits (RPM / TPM)	5,000 – 15,000 RPM (Production Tier) · 800,000 – 2,000,000 TPM	4,000 – 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 window	Standard rate up to 200K tokens; 2x input/output tier above 200K tokens
Prompt Cache Policy & TTL	Cached input at $0.5/1M tokens	$0.4/1M cached read (90% off); 5-min default & 1-hour extended TTL
Computer Use / GUI Agent	API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)	Supported (Screen coordinate grounding, browser & desktop GUI action loops)
MCP & Parallel Tool Calling	Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema	Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & Sandbox	Real-time Web & X (Twitter) Search Grounding + Code Execution	Native Web Search Citations + Code Execution Tool + MCP Connectors
Official Fine-Tuning Support	API Prompt Engineering & RAG Distillation	Custom Model Tuning via Amazon Bedrock & Prompt Distillation
Multimodal Token Billing	Text 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 VRAM	Cloud-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 Classification	xAI Production Safety & Alignment Verified	Anthropic 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 Tier	SOC2 Type II · GDPR · Zero Data Retention (ZDR) & HIPAA BAA Available on Enterprise Tier
Input Modalities	text, vision	text, vision
Output Modalities	text	text

Grok 4.7 vs Claude Opus 5.5: Risposte Rapide (FAQ)

Which is more intelligent, Grok 4.7 or Claude Opus 5.5?

Claude Opus 5.5 is more intelligent. It scores 94 compared with 46 on the composite Intelligence Index.

Which model is faster?

Grok 4.7 is faster, generating 110 tokens per second compared with 78 tokens per second.

Which model is cheaper to run?

Grok 4.7 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 4.7 has lower latency, with a time to first token of 0.62s 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.

Verdetto

Sia Grok 4.7 (Ideale per il ragionamento aziendale di frontiera, la programmazione avanzata e i carichi di produzione, sistemi RAG aziendali e integrazioni API scalabili.) sia Claude Opus 5.5 (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: Claude Opus 5.5 guida nei benchmark di ragionamento e programmazione, Grok 4.7 garantisce una generazione più rapida e Grok 4.7 offre il miglior rapporto qualità-prezzo per carichi API elevati.

Domande Frequenti (FAQ)

Quale modello è migliore per coding e ragionamento, Grok 4.7 o Claude Opus 5.5?+

Nell’indice di intelligenza composito e nei benchmark di programmazione prevale Claude Opus 5.5. Consulta i punteggi SWE-bench e GPQA qui sopra per tutti i dettagli.

Qual è la differenza di prezzo API tra Grok 4.7 e Claude Opus 5.5?+

Grok 4.7 costa $2.00 / $6.00 per milione di token di input/output, mentre Claude Opus 5.5 costa $4.00 / $20.00. Nel costo combinato, Grok 4.7 risulta più economico.

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

Grok 4.7 supporta 500K token di contesto contro 1M token di Claude Opus 5.5, mentre Grok 4.7 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 & Pricing Context Window AI Benchmarks Reasoning Models Tool Calling Model Context Protocol (MCP)

Grok 4.7 vs Claude Opus 5.5

Cambia e Confronta Qualsiasi Modello

Grok 4.7

Claude Opus 5.5

Chi vince in ogni categoria?

Punteggi Benchmark Verificati

Latenza e Tempo di Risposta

Simulatore Interattivo dei Costi Token

Grok 4.7 · Strengths & Key Advantages

Considerations & Trade-offs

Claude Opus 5.5 · Strengths & Key Advantages

Considerations & Trade-offs

Token Use & Task Economics

Specifiche Tecniche

Grok 4.7 vs Claude Opus 5.5: Risposte Rapide (FAQ)

Verdetto

Domande Frequenti (FAQ)

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